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Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required. What to expect A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers Access to Claude models and GPU compute Connection to the broader AI safety and security research community Interview process The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check. Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027. You may be a good fit if you Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into working on empirical AI research full-time Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer) Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases Mentors and research areas Potential Anthropic mentors include: Sara Price : leads the Alignment Training team; background in data science Ethan Perez : leads the Alignment Science team; background in machine learning Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI) Samuel Marks : leads the Scalable Oversight team; background in mathematics Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT) Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include: AI safety & alignment Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. AI security & frontier red-teaming Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography. ML systems & reinforcement learning Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines. For a fuller picture of the questions we care about, see our Recommendations for Technical AI Safety Research Directions and recent publications from our Alignment , Interpretability and Frontier Red teams. Logistics Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception. Location: We prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire. Commitment: Full-time role for the duration of the residency. Compensation: $350,000 to $500,000/year pro-rated for the duration of the residency + benefits Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire. Applicants may also be considered for the Anthropic Fellows Program . The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role AI has the power to dramatically accelerate the pace of scientific discovery and the development of healthcare interventions. Alongside the models and tools we build for scientists, Anthropic’s life science research teams now run their own wet lab experiments. We’re hiring a life sciences patent counsel to work side-by-side with our researchers as they work to advance biomedical progress. You will manage patent strategy and filings for our life sciences research, from the first conversation with a scientist through global prosecution. You will also be our in-house expert on the patent questions, many of them new, that arise when scientists use AI as a research tool. You will partner closely with our patents lead (direct manager), the Head of IP, Research Legal, our Life Sciences Counsel, and outside counsel to design and implement a patent program that supports our researchers and partners and is aligned with the company’s mission. Responsibilities Manage patent strategy and filings for Anthropic’s life sciences research in the U.S. and internationally, including invention harvesting, filing decisions, drafting oversight, prosecution, and management of outside counsel Serve as the trusted patent advisor to our life science research teams, and design and implement scalable guidance and processes to support our fast-growing life science efforts Make inventorship determinations for AI-assisted research, and advise on inventor declarations and the duty of candor Develop claim and filing strategies across biological and chemical inventions, platform technologies, and computational methods, accounting for written description, enablement, eligibility, and obviousness Partner with Research Legal and Communications on the timing of publications, preprints, presentations, and open-source releases Advise on the patent aspects of agreements with life science and biopharma counterparties, including ownership of inventions and improvements, and support patent diligence and freedom-to-operate analyses for our research Anticipate emerging legal developments affecting AI technologies in the life science and biopharma space and provide strategic guidance to leadership Minimum qualifications Hold a law degree (JD, LLB, or equivalent) and meet the local licensing requirements to work as in-house counsel where you'll be based A degree or equivalent training in a life sciences or chemistry field (for example, molecular biology, biochemistry, genetics, bioengineering, or organic chemistry) Substantial hands-on experience drafting and prosecuting U.S. life sciences patent applications, and directing foreign prosecution through local counsel Lead responsibility for a patent portfolio, including managing budget and outside or foreign counsel Experience making inventorship determinations and resolving ownership questions in multi-party research arrangements (for example, with universities and other partners) Excellent communication skills, with the ability to translate legal risk into practical guidance for scientists, researchers, and business partners A low-ego, high-empathy orientation and a “doer” attitude: willing to roll up your sleeves and pitch in where needed Intense curiosity about AI and science, and a commitment to responsible AI development Preferred qualifications 10+ years of patent experience (including time as a patent agent, technical specialist, or examiner) at a law firm, a biotech or pharmaceutical company, or both, with the ability to operate independently and hit the ground running Advanced degree in a life sciences or chemistry field Experience with AI/ML companies, or with inventions at the boundary of biology and machine learning Working knowledge of how patents interact with regulatory exclusivity, trade secrets, and open science Familiarity with biosecurity, dual-use research, or export control considerations in the life sciences Experience leveraging AI to optimize their work, with a desire to work in a fast-paced, innovative environment The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $335,000 — $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Anthropic is looking for an Applied AI Engineer to help partners use Claude for clinical development and rare-disease research.

Location: Lanham, MD Luminis Health Title: Sterile Processing Technician II Department: Central Sterile Processing Job Code: 000333 FLSA Status: Non-Exempt Position Objective: The objective of this position is to assemble and sterilize all instruments, instrument trays, utensils, and linen packs. Perform distribution functions as it relates to case carts and sterile instrumentation. Must be able to perform all Sterile Processing functions. The position requires rotating weekend and on-call requirements. A strict dress code and professional appearance including wearing surgical scrubs are required. Essential Job Duties: Reasonable accommodation may be made to enable individuals with disabilities to perform essential functions. Uses established departmental and regulatory standards, principles, and procedures for aseptic technique. Processes and assembles instrument trays, respiratory/anesthesia equipment, linen, and utensils accurately and promptly. Uses established schedule to operate steam and plasma sterilizer. In addition, loads unload and move sterilizer carts. Runs verify and record necessary tests on all steamed and plasma equipment used in the department. Ensures that Bowie-Dick removal test is run on pre-vacuum steam sterilizer each morning and after repairs. Reports all malfunctions to the biomedical department, department supervisor, and the O.R. supervisor. Precepts and verifies competency and skill development of staff as appropriate providing meaningful feedback to Training and Staff Development Coordinator and Clinical Operations Supervisor or Manager. Perform spot checks of paperwork, labeling, and biological reads. Inspects packages to ensure all external indicators, filters, and/or labels are securely affixed to items, returns non-satisfactory products to the instrument room. Performs (HLD) High level disinfection with 100% accuracy. Utilizes patient-specific pick lists to accurately gather surgical instruments and disposable supplies requested by the attending surgeon or another Peri-Operative representative. Documents case cart build process in SPM, continuously updating the record as items are fulfilled to maintain the integrity of the needs list. And responds to OR requests and participates in OR huddles as needed. Communicates unmet surgical supply requests to leadership for resolution assistance. Utilizes patient-specific pick lists to accurately gather surgical instruments and disposable supplies requested by the attending surgeon or another Peri-Operative representative. Documents case cart build process in SPM, continuously updating the record as items are fulfilled to maintain the integrity of the needs list. Performs scheduled and cyclic physical inventory of supplies and instruments within the department. Educational/Experience Requirements: Required Minimum Education : High school diploma or equivalent. PREFERRED Experience : Completion of a Central Sterile Processing program through an accredited institution.  Two years of experience as a sterile processing technician. Advancement to tech II based on department needs, competency and performance. Required License / Certifications: Certified Registered Central Service Technician (CRCST) or CBSPD certification preferred Working Conditions, Equipment, Physical Demands : There is a reasonable expectation that employees in this position will be exposed to blood-borne pathogens. Physical Demands – Medium work . Exerting up to 50 pounds of force occasionally, and/or up to 30 pounds of force frequently, and/or up to 10 pounds of force constantly to move objects. Must be able to frequently lift to 35 lbs. stoop, bend, pull, and place and retrieve material. There is reasonable expectation that employees in this position will be exposed to blood-borne pathogens. The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements. Pay Range $20.65 — $25 USD Luminis Health Benefits Overview: •    Medical, Dental, and Vision Insurance •    Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year) •    Paid Time Off •    Tuition Assistance Benefits •    Employee Referral Bonus Program •    Paid Holidays, Disability, and Life/AD&D for full-time employees •    Wellness Programs •    Employee Assistance Programs and more *Benefit offerings based on employment status Opt-in for text notifications! Luminis Health's two-way SMS texting platform lets you receive notifications and messages from our Talent Acquisition team directly on your phone. To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time. Standard text messaging rates may apply based on the candidate's mobile carrier plan. Luminis Health is not responsible for any charges incurred by the recipient. Candidates are encouraged to review their mobile carrier's plan for applicable text messaging rates and usage charges.

Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Collaborate with Product Managers and Delivery Leads to define, refine, and prioritize product requirements Gather, analyze, and document business requirements, user stories, acceptance criteria, and business processes Conduct stakeholder interviews, workshops, and user feedback sessions to understand business and user needs Translate requirements into well-structured Jira epics, features, user stories, and tasks Work closely with UX/UI Designers to define user journeys, personas, workflows, and usability requirements Collaborate with engineering and data teams to clarify requirements and support iterative Agile delivery Support the design and validation of AI-powered workflows, including agentic AI interactions and business processes Create and maintain product requirements, process documentation, and knowledge-base materials in Confluence Partner with QA teams to define test scenarios, acceptance criteria, and validation approaches Collect, analyze, and manage user feedback, enhancement requests, and product improvement opportunities Support product releases, user adoption, rollout, and change management activities Maintain a well-structured and prioritized product backlog in collaboration with stakeholders What we expect : 3+ years of experience as a Business Analyst working on software development or digital product delivery projects Experience working in the Life Sciences, pharmaceutical, biotechnology, healthcare, or biomedical research domains Practical experience supporting the delivery of AI-powered applications or solutions Strong understanding of Agile methodologies, including Scrum and/or Kanban. Hands-on experience with Jira and Confluence Proven experience gathering, analyzing, and documenting business requirements, user stories, and acceptance criteria Experience collaborating with cross-functional teams, including Product Management, UX/UI, Engineering, and QA Experience supporting the end-to-end software development lifecycle, from discovery and requirements gathering through testing and release Strong analytical thinking and ability to translate complex or ambiguous business needs into clear, actionable requirements Experience facilitating workshops, stakeholder interviews, and requirements review sessions Excellent communication, documentation, and stakeholder management skills Strong English communication skills Nice to have : Experience working on Agentic AI, or Generative AI (LLM-based) applications Understanding of AI concepts and technologies, including Retrieval-Augmented Generation (RAG), knowledge graphs, semantic search, and metadata management Experience delivering data-centric products, such as data catalogs, data discovery platforms, or scientific knowledge management solutions Familiarity with clinical data management concepts, including real-world data (RWD) and real-world evidence (RWE). Understanding clinical data governance, privacy regulations, and compliance requirements, including GDPR and HIPAA, in the scope of development of AI solutions. Ability to interpret and integrate molecular, clinical, and diagnostic data to support research and healthcare applications. Experience supporting multiple products or workstreams simultaneously We offer : Competitive compensation Remote work Flexible working hours Continuous education, mentoring, and professional development programs A team with excellent tech expertise

Location: Indianapolis, United States; Ohio City, United States; Chicago, United States Description Location: Indianapolis, IN Metro (Hybrid / 3-Day Onsite) (Open to Regional/EST Candidates with Onsite Travel) Contract Type: Contractor Full-Time / Enterprise Project Engagement (Outsourced via Xenon7) About Xenon7 Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth. Role purpose Lead the development and application of digital twins to improve clinical trial design and support evidence-based clinical development decisions. The role prioritizes digital-twin, simulation, and AI/ML expertise, supported by clinical-development experience and close partnership with trial-design experts. Position overview You will join a multidisciplinary clinical development environment and partner with clinical scientists, physicians, biostatisticians, pharmacometricians, biomarker experts, data scientists, data engineers, and other stakeholders. You will translate clinical development questions into quantitative strategies and deliver  interpretable analyses that inform protocol design, patient selection, endpoint strategy, dosing, operational planning, and decision-making under uncertainty. The role prioritizes digital twins as the primary capability for simulating patients, disease trajectories, treatment response, and clinical trials. The successful candidate will bring strong digital-twin, simulation, and AI/ML expertise, along with sufficient clinical-development knowledge to work effectively with trial teams. Deeper trial-design expertise can be developed through close collaboration with clinical scientists, biostatisticians, and pharmacometricians. Key responsibilities Digital-twin development and validation ·   Lead the design, development, and evaluation of digital twins of patients, disease trajectories, treatment response, or clinical trials using clinical trial and relevant external data. ·   Combine mechanistic, statistical, causal, and machine learning approaches to create fit-for-purpose digital twins that can be simulated under alternative populations, interventions, dosing strategies, endpoints, or trial designs. ·   Define use cases and contexts of use with clinical and quantitative experts so each digital twin addresses a specific trial-design or development decision. ·   Assess calibration, validation, robustness, transportability, uncertainty, and practical relevance using appropriate internal and external evaluation strategies. ·   Develop reproducible workflows and reusable digital-twin components that can be applied across programs or therapeutic areas. Clinical trial design and quantitative decision support ·   Partner with trial teams to frame development questions and evaluate design options, including target populations, eligibility criteria, enrichment strategies, comparators, endpoints, visit schedules, dosing strategies, and operational tradeoffs. ·   Use digital twins and complementary simulation methods to compare plausible scenarios, characterize uncertainty, and support model-informed decision-making. ·   Work closely with statisticians and pharmacometricians so analyses complement established trial-design methods and align with clinical and regulatory objectives. ·   Communicate assumptions, limitations, and decision-relevant insights clearly to technical and non-technical stakeholders. Data integration and scientific collaboration ·   Analyze and integrate clinical trial data and, where relevant, biomarkers, imaging, digital health data, omics, patient-reported outcomes, and real-world data. ·   Partner with data engineering and platform teams to create analysis-ready datasets, data-quality checks, lineage, and reproducible pipelines. ·   Contribute to scientific documentation, presentations, publications, and responsible adoption of digital-twin methods across clinical development. Model quality and responsible use ·   Define the intended use, decision context, success criteria, and limitations of each model before development. ·   Ensure models are interpretable, auditable, reproducible, and supported by evidence appropriate to their intended use. ·   Apply appropriate governance, privacy, security, and scientific-review requirements for clinical data and analytical outputs. ·   Clearly distinguish exploratory analyses from validated decision-support evidence and avoid overclaiming model capability. Requirements ·   PhD in data science, statistics, biostatistics, pharmacometrics, computer science, biomedical informatics, engineering, mathematics, operations research, or a related quantitative field. ·   Demonstrated experience developing digital twins, virtual patients, disease-progression models, clinical trial simulations, synthetic controls, or closely related computational models. ·   Strong experience applying machine learning, statistical modeling, causal inference, or simulation to biomedical, healthcare, pharmaceutical, or other complex scientific data. ·   Strong programming skills in Python, R, or a comparable analytical language, with experience using version-controlled and reproducible workflows. ·   Sufficient clinical-development knowledge to frame relevant questions and collaborate effectively with clinical and quantitative trial experts. ·   Ability and interest to deepen clinical trial-design knowledge through partnership with clinical scientists, biostatisticians, and pharmacometricians. ·   Strong written and verbal communication skills and demonstrated effectiveness in cross-functional scientific collaboration. Preferred qualifications ·   Strongly preferred: experience supporting clinical trial design, protocol development, clinical development strategy, model-informed drug development, or regulatory-facing quantitative evidence. ·   Familiarity with one or more trial-design topics, such as endpoint strategy, sample size or power assumptions, patient selection or enrichment, longitudinal outcomes, missing data, adaptive designs, or decision criteria. ·   Knowledge of digital-twin architecture and validation, supported by expertise in causal inference, Bayesian modeling, survival analysis, longitudinal modeling, clinical trial simulation, or synthetic controls. ·   Experience with clinical data standards and common clinical-development data sources. ·   Experience with biomarker, imaging, omics, digital health, or real-world data and integration of multiple data modalities. ·   Experience with scalable cloud-based analytical environments. ·   Track record of translating analytical work into decisions, reusable capabilities, publications, presentations, or other measurable scientific impact.

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies, behaviors, and daily lives.   WHOOP Labs is the on-site research facility for product development and innovation at WHOOP. We conduct human-centered hardware and algorithm research to create best-in-class product experiences that work for all members.   WHOOP is hiring a Researcher II to support research planning and execution on weekends, supporting critical data collection windows for participant diversity and expanded access. This role will cover a broad range of research studies for algorithm training, hardware validation, and design testing. While your home base will be WHOOP’s on-site product research facility, WHOOP Labs, studies will include field collections across the metro Boston area to widen access for diverse communities. Your efforts will support the organization as we continue to develop a best-in-class experience and lead the wearables industry.   *This role is fully onsite at our Boston, MA office and follows a 4x10 schedule, with four 10-hour workdays each week, Friday through Monday, and three days off Tuesday through Thursday.   RESPONSIBILITIES - Execute testing protocols across multiple concurrent studies, owning research execution on weekends and collaborating with other researchers on Friday and Monday to ensure consistent protocol administration across all days and shifts. - Own research documentation for weekend hours, collaborating with other researchers on Friday and Monday to ensure effective handoffs and information transfer across shifts. - Provide coaching and guidance to participants during exercise protocols, balancing data integrity, research best practices, and participant experience - Create a supportive and welcoming environment for participants engaging in a range of research tasks, from exercises to device interactions - Manage the use, troubleshooting, and upkeep of sensitive data collection equipment and prototype devices - Develop strong working knowledge of WHOOP’s research platform tooling suite, with the ability to troubleshoot issues in real time—including during active data collections—and problem-solve on the fly - Develop junior researchers by providing technical coaching, delegation, constructive feedback, and growth opportunities - Own daily lab management tasks required for data collections to be successful, such as laundry, equipment cleaning, material organization, and overall lab readiness - Serve as an ambassador for WHOOP Labs and the WHOOP brand   QUALIFICATIONS - Bachelor’s Degree in human physiology, biomedical engineering, psychology, HCI, or similar - Professional experience in research & development, human subjects research, or a related field, including 2+ years of experience conducting human subjects research - Strong technological background and working knowledge of data management systems including the Google Suite - Familiarity with research platform tools and hardware testing environments preferred - Strong interpersonal communication skills with a savvy for working as part of a highly collaborative, fast-paced team - Ability to manage multiple priorities and adapt quickly in dynamic research settings - Prior experience in customer service or other public-facing roles a plus - Strong written, verbal, and presentation skills, with confidence giving and receiving feedback across disciplines   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $75,000 - $95,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep. The Health team develops the algorithms and features that expand WHOOP's health sensing capabilities. The work spans women's health, software as a medical device, wellness and longevity, member insights, and emerging health signals. We combine continuous physiological data with clinical research and domain expertise to ship features that are scientifically grounded and useful to millions of members. As a Staff Applied Machine Learning Scientist on the Health team, you will turn ambiguous clinical and product questions into defensible studies, models, and evaluation plans on WHOOP's longitudinal wearable and member data (physiological signals, behavioral logs, labs and integrations, and related streams). You will set the methodological bar for a Health domain. You will partner with Machine Learning Engineers on the path to production, and with Product, clinical, and Digital Health partners on what the data can and cannot support. Success in this role requires applied algorithm and statistical craft, the judgment to operate across Health problem types, and Staff-level leadership: launching domain work independently, raising the quality and velocity of the people around you, and making clear prioritization calls under uncertainty. RESPONSIBILITIES - Lead the design, development, and validation of machine learning and statistical methods for Health features, using wearable physiological and behavioral data and related member sources. - Frame ambiguous health and product questions into well-scoped modeling or study problems, with clear performance criteria, evaluation plans, and honest treatment of uncertainty and failure modes. - Set the methodological and quality standard for a Health domain: reusable evaluation practices, review expectations, and documentation that others can inherit. - Develop and refine approaches for time-series, longitudinal, and multimodal data, including data curation, labeling strategy, feature and representation choices, and offline evaluation that holds up under real-world noise, missingness, and population shift. - Partner with Machine Learning Engineers to translate validated methods into production-ready systems, making modeling choices that account for scalability, reliability, latency, cost, monitoring, and (where relevant) controlled-release constraints. - Serve as a technical counterpart to Product and Digital Health (clinical science, regulatory, quality): pressure-test performance requirements, study design, and evidence quality, and push back when a claim is not supportable. - Raise the quality and velocity of the scientists and engineers around you through design reviews, mentorship, and the judgment of when to coach someone else to champion a problem versus taking it yourself. - Communicate trade-offs, risks, and results clearly to technical, clinical, product, and leadership audiences; prevent misalignment early; drive decisions with evidence and a clear point of view on domain direction. QUALIFICATIONS - Master's or PhD (or equivalent professional experience) in Biomedical Engineering, Electrical Engineering, Computer Science, Applied Mathematics, Biostatistics, Bioinformatics, Physiology, or a related quantitative or health-science field. - 7+ years of professional experience developing algorithms, applied ML models, or statistically rigorous analyses in health, wearables, medical devices, digital health, or a closely related domain. - Demonstrated Staff-level technical leadership: setting methodological standards others reuse, influencing multi-team outcomes, mentoring senior ICs, and making prioritization calls under uncertainty. End-to-end project ownership alone is not sufficient. - Strong foundation in statistics (Bayesian and frequentist) and machine learning for time-series and longitudinal data, with the ability to draw defensible conclusions from observational, noisy, or otherwise messy real-world data. - Experience with wearable or physiological signals (PPG, IMU, HR/HRV, sleep, activity, temperature, or similar) or a closely related adjacent time-series domain. - Hands-on experience designing studies or evaluation protocols end-to-end: data curation, metric choice, validation splits, subgroup and failure analysis, and documentation of assumptions and limitations. - Strong Python skills with reproducible scientific / ML engineering hygiene (clean, reviewable code; comfort with stacks such as NumPy/SciPy/pandas, scikit-learn, PyTorch/TensorFlow). - Clear, high-signal communicator who can move between deeply technical method discussions and cross-functional conversations with Product, clinical partners, and leadership. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. The Health team develops the algorithms and features that expand WHOOP's health sensing capabilities. The work spans women's health, wellness and longevity, member insights, emerging health signals, and software as a medical device. Applied ML Scientists and ML Engineers work as a production unit: scientists own problem framing and modeling; engineers own the path to production. As a Senior Manager, Machine Learning on the Health team, you will own delivery and people outcomes across a mixed team of scientists and engineers. You will translate department strategy into clear quarterly plans, develop senior ICs (and, as the team grows, the next layer of managers), hire against a high bar for both crafts, and partner with Product and adjacent Health partners on what is worth building and what the data can support. You will stay close enough to the ML lifecycle to evaluate the team's most important decisions without becoming the default contributor. Success in this role requires enough ML and health-domain fluency to earn trust from senior ICs, plus the people-leadership skill to grow that team, hold delivery across multiple workstreams, and make prioritization calls under uncertainty. RESPONSIBILITIES: - Own delivery, team health, and people outcomes across Health ML workstreams on a mixed Applied ML Scientist and ML Engineer team. - Translate department strategy into quarterly plans, milestones, and success criteria; keep the team on the highest-leverage work and adapt deliberately as priorities shift. - Build the team: lead hiring across science and engineering roles, calibrate the bar for each craft, and shape onboarding, leveling, and growth practices. - Develop the next layer of leadership: coach senior ICs (and managers, as the scope grows), manage performance with clarity and care, and create the conditions for people to operate above their level. - Set the standard for how Health ML gets built: work quality, evaluation rigor, review practices, and an operating model that holds as people and workstreams change. - Partner directly with Product (and with clinical, software, and Digital Health partners as the work requires) to align on roadmap, evidence, and sequencing; broker trade-offs between iteration speed, scientific integrity, and member value. - Own the risk posture for the team: anticipate execution, technical, and people risks, design mitigation into how the team operates, and keep senior leadership clearly informed of the most consequential decisions. - Define and own the operating model: planning cadences, design reviews, decision forums, and quality gates appropriate to member-facing health ML. - Build and continuously raise AI-enabled workflows that create measurable leverage across the team, for development, evaluation, documentation, and stakeholder communication. - Represent the team's work credibly to executive and cross-functional audiences with brevity, evidence, and clarity. QUALIFICATIONS: - 7+ years of experience in machine learning, applied science, or software engineering, with 3+ years managing engineering and/or science teams. - Bachelor's degree in Computer Science, Engineering, Applied Math, Biomedical Engineering, or a related field; advanced degree preferred. - Demonstrated track record managing highly senior ICs: hiring, performance management, and developing people who in turn raise the bar around them. - Deep familiarity with the ML development lifecycle (data collection, model training, evaluation, validation, deployment, and monitoring), sufficient to evaluate the most important technical and methodological decisions the team makes. - Experience shipping algorithms or ML-enabled product in health, wearables, digital health, or a closely related applied domain. - Demonstrated ability to set direction and make timely prioritization calls under uncertainty, keeping team focused on the highest-leverage work. - Demonstrated AI-tooling sophistication: a track record of building or adopting AI-enabled workflows that materially improved team speed, quality, or decision confidence. - Clear, high-signal communicator who can move fluidly between technical ML discussions and executive-level summaries of risk, trade-offs, and direction. - Depth in a Health domain WHOOP already works preferred (member insights, women's health, cardiometabolic or respiratory health, sleep, strength / healthspan, neuroscience, or related physiological time-series work). - Preferred experience as a counterpart to Product on ambiguous health or member-insight problems: scoping, sequencing, and pushing back when a claim is not supportable. - Familiarity with clinical validation, evidence packages, or Digital Health partnership on higher-stakes regulated health features preferred.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $170,000 - $230,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.   Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep. We are seeking a Senior Signal Processing Engineer to develop and deploy algorithms for physiological sensors including optical sensor and inertial measurement unit (IMU) data into accurate, reliable, and real-time insights on WHOOP devices. This hands-on role centers on digital and statistical signal processing, sensor fusion, and model-based state estimation, with a particular focus on accelerometer and gyroscope data. You will own algorithm development from sensor characterization, mathematical modeling, and Python prototyping through efficient C/C++ implementation, firmware integration, and production validation. Working closely with Firmware, Hardware, Data Science, and Product, you will deliver robust on-device algorithms that perform reliably across diverse members and real-world conditions while meeting the constraints of wearable hardware. RESPONSIBILITIES - Design and develop real-time signal processing and sensor fusion algorithms that combine Sensor measurements inputs to characterize motion and deliver reliable member-facing insights. - Develop and tune model-based estimators for orientation and motion, including sensor bias estimation, uncertainty propagation, and drift mitigation under changing movement and sensing conditions. - Build robust IMU processing pipelines, including filtering, calibration, time synchronization, resampling, coordinate transformations, and compensation for sensor noise and systematic errors. - Analyze large-scale, noisy wearable datasets to identify failure modes and improve robustness across motion patterns, device orientation, fit, and individual movement characteristics. - Translate algorithm prototypes into production-ready C/C++ implementations, balancing accuracy with power, memory, compute, numerical stability, and latency. - Partner with Firmware and Hardware teams on sensor configuration, sampling strategies, and on-device integration; investigate differences between prototype behavior and performance on target hardware. - Define performance metrics and rigorous validation plans using reference measurements, controlled experiments, real-world data, and on-device testing to assess accuracy, robustness, and long-duration stability. - Own technical decisions for complex algorithm components, contribute to design and code reviews, mentor teammates, and collaborate across functions to investigate post-deployment issues and drive continuous improvement. QUALIFICATIONS - 5+ years of experience developing and deploying signal processing, sensor fusion, or state-estimation algorithms for real-world sensor applications, including substantial hands-on work with IMU data. - MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics, or a related quantitative field, or equivalent practical experience. - Strong foundation in digital and statistical signal processing, including filtering, spectral analysis, stochastic processes, and sensor noise characterization. - Demonstrated experience with accelerometer and gyroscope processing, IMU calibration, sensor error modeling, bias estimation, and drift management. - Strong experience with Kalman filtering, including extended or error-state formulations, and model-based sensor fusion; practical understanding of nonlinear estimation, uncertainty propagation, and estimator failure modes. - Practical knowledge of 3D motion and orientation representations, including coordinate frames, rotation matrices, quaternions, and rigid-body kinematics. - Proficiency in Python for algorithm development, data analysis, and experimentation, and C/C++ for efficient embedded implementation; demonstrated experience deploying algorithms to resource-constrained hardware. - Ability to independently investigate complex algorithmic problems, design rigorous validation experiments, and communicate technical tradeoffs with firmware, hardware, and cross-functional partners. - Experience with body-worn sensors, human-motion modeling, motion segmentation, or periodicity analysis is highly desirable. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Location: London, UK About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team. This is a partner-facing role: you'll support nonprofits, research institutes, academic medical centres and public-sector funders as they use Claude to get treatments to patients with rare and neglected diseases, where there is little or no commercial incentive to fund development. The role focuses on clinical development, where we think Claude can help these partners today. Trials in these diseases have small patient populations, investigator-led or nonprofit funding and little operational support, and they often stall on protocol quality, operational risk and site start-up. Claude can help teams design better trials and start them sooner. Much of this work is drug repurposing: testing new uses for approved, usually off-patent or generic medicines, whose known safety profiles can let a good hypothesis reach patients years sooner than a new molecule. You'll advise and embed in partners' teams, building alongside their engineers, scientists and clinicians. Responsibilities Work with partners' trial teams to design, review and prioritise clinical trials with Claude: drafting and reviewing protocols and statistical analysis plans, and flagging enrolment and operational risks. Build and validate tools that help partners find new uses for approved, mostly off-patent medicines in rare and neglected diseases, from literature, omics and patient data, and assemble the evidence so the partner can decide the next step. Build reusable infrastructure other institutions can adopt (MCP servers for biomedical data sources, agent skills, benchmarks grounded in real clinical questions), and feed what you learn in the field back to product, engineering and research. You Might Be a Good Fit If You Have Hands-on clinical development experience: designing, running or analysing clinical trials, or assessing clinical evidence to decide which programmes go forward (for example due diligence or asset evaluation). Drug repurposing work as part of that is a strong plus, as is having contributed to a regulatory submission for a trial. Comfort with biomedical data: literature, omics, and real-world patient data (health records, registries, claims), ideally inside secure or trusted research environments. Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure it. Experience working directly with external partners or customers in a technical role. Clear written and verbal communication: docs other institutes can use without you, and results clinicians trust. A scrappy mentality: you're comfortable in ambiguity, wear several hats, and do what it takes to get a result for a partner. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £225,000 — £255,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep. We are seeking a Staff Applied Machine Learning Scientist to develop and continuously improve production-ready edge algorithms that transform sensor data into accurate, reliable, and real-time physiological insights. In this role, you will develop innovative approaches that combine deep learning, machine learning, and signal processing to deliver meaningful value to WHOOP members while optimizing for accuracy, latency, power, and scalability across wearable platforms. You will work closely with a cross-functional team of scientists, engineers, physiologists, and hardware experts to solve challenging problems at the intersection of wearable sensing, physiological modeling, and applied AI. You will develop novel modeling approaches, and own complex algorithmic problems from early development through production deployment and continuous improvement. Your work will directly shape the future of WHOOP’s sensing capabilities and our ability to provide members with accurate, personalized, and actionable insights into their health and performance. RESPONSIBILITIES: - Design advanced algorithms that combine signal processing, physiological modeling, machine learning, and deep learning for physiological time-series and multimodal sensor data, with a focus on accuracy, robustness, and generalization across diverse members and real-world conditions. - Own the development and continuous improvement of production-ready edge algorithms that transform multimodal sensor data into accurate, reliable, and real-time physiological insights. - Analyze large-scale wearable sensor datasets to identify performance gaps, characterize challenging conditions, and drive data-informed algorithm improvements. - Define rigorous evaluation methodologies, validation frameworks, and performance metrics to assess algorithms throughout development and deployment. - Optimize algorithms for embedded deployment, balancing accuracy with power, memory, latency, and compute constraints across current and future wearable platforms. - Set technical direction and establish best practices for modeling, experimentation, validation, and algorithm development across complex sensing problems. - Pursue ambiguous, high-impact technical initiatives from research and prototyping through validation, production deployment, monitoring, and continuous improvement. - Collaborate closely with Data Science, Firmware, Software, Hardware, Product, and domain experts to translate algorithmic innovations into production-ready capabilities and member-facing features. - Stay at the forefront of advances in deep learning, machine learning, signal processing, edge AI, and physiological sensing, and translate relevant innovations into differentiated WHOOP capabilities. QUALIFICATIONS: - MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field. - 7+ years of experience developing and deploying machine learning, deep learning, and/or signal processing algorithms for complex real-world applications. - Deep technical expertise in modern machine learning and deep learning methods, particularly for time-series and multimodal sensor data. - Strong foundation in digital and statistical signal processing, with the ability to combine classical signal processing techniques with modern learning-based approaches. - Strong proficiency in Python for algorithm development, experimentation, and large-scale data analysis; experience with C/C++ and embedded algorithm development is highly desirable. - Demonstrated ability to develop robust models using large, noisy, real-world datasets and achieve strong generalization across diverse conditions. - Experience designing rigorous experiments, defining performance metrics, performing error analysis, and translating findings into algorithm improvements. - Experience taking algorithms through the full development lifecycle, from research and prototyping through validation, deployment, monitoring, and continuous improvement. - Strong analytical and problem-solving skills, with the ability to navigate ambiguity and make sound technical decisions. - Experience with physiological signals, wearable sensors, or biomedical sensing is highly desirable. - Experience optimizing algorithms for resource-constrained embedded or edge environments, including tradeoffs across accuracy, power, memory, compute, and latency, is a plus. - Strong commitment to embracing and leveraging AI tools in day-to-day work while maintaining high standards for quality and rigor. Join us in pushing the boundaries of wearable sensing, applied AI, and physiological intelligence and positively impacting people’s lives! This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. By combining advanced sensing, data science, and technology designed for continuous wear, WHOOP delivers insights that help members better understand and improve their health and performance. WHOOP is looking for a Senior Sensor Intelligence Engineer to join our Embedded Controls team within Sensor Intelligence and help shape the sensing capabilities across current and future WHOOP devices. Sitting at the intersection of signal processing, machine learning, embedded systems, and sensor technology, you will develop algorithms that interpret real-world sensor signals and intelligently control how sensors operate on-device. You will work across the sensing stack from understanding sensor physics and signal characteristics through algorithm development and embedded deployment to enable increasingly sophisticated sensing capabilities while meeting the power, compute, memory, and reliability constraints of a continuously worn device. RESPONSIBILITIES: - Develop signal-processing and machine-learning algorithms that interpret physiological, motion, and other wearable sensor signals, including applications such as activity and state detection, wear detection, signal-quality assessment, and device-state estimation - Design intelligent embedded control strategies that dynamically configure sensor behavior based on signal quality, device state, user context, system requirements, and power constraints - Characterize new and existing sensors by understanding signal behavior, noise sources, artifacts, dynamic range, sampling requirements, calibration, operating modes, and the impact of analog and acquisition architectures - Prototype algorithms and sensing strategies using tools such as Python or MATLAB, then partner with Firmware Engineering to translate them into robust, computationally efficient implementations suitable for resource-constrained embedded systems - Partner closely with Firmware, Electrical Engineering, Data Science, Hardware, and broader Sensor Intelligence teams to bring up new sensing modalities, debug issues across the sensing stack, and inform sensing architectures for future WHOOP products - Develop experiments, analysis frameworks, and validation methodologies to evaluate sensor and algorithm performance across users and real-world conditions, optimizing solutions for accuracy, robustness, latency, memory, compute, and power QUALIFICATIONS: - BS, MS, or PhD in Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Applied Physics, or a related technical field, or equivalent practical experience - Strong foundation in digital signal processing and time-series analysis, with experience applying techniques such as filtering, spectral analysis, sampling theory, noise reduction, and feature extraction to real-world sensor data - Experience developing signal-processing and/or machine-learning algorithms for noisy, artifact-prone sensor data and taking algorithms beyond offline analysis toward real-time, embedded, or production implementation - Strong proficiency in Python, MATLAB, or similar algorithm-development environments, with working knowledge of C/C++ and embedded-system considerations such as timing, memory, compute, and hardware interfaces - Working knowledge of sensor and electrical systems, including concepts such as ADCs, analog front ends, sampling, digital interfaces, noise, calibration, and signal acquisition - Ability to investigate and solve ambiguous engineering problems across algorithm, firmware, sensor, and electrical boundaries using strong experimental and analytical methods - Experience with wearable, physiological, optical, impedance, motion, multimodal, or related sensor systems is valued; experience with embedded inference, sensor fusion, fixed-point processing, quantization, low-power sensing, or microcontroller deployment is a plus - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Location: United States The Company: Our client is a digital cardiology start-up headquartered in Berlin and Boston, focused on developing innovative technology to improve outcomes for patients living with heart failure. It has already deployed a CE-marked remote patient monitoring platform across Europe and is now advancing a voice-based Software as a Medical Device designed to detect worsening heart failure through short, daily smartphone recordings. Its voice-based solution has received FDA Breakthrough Device Designation, with its pivotal FDA trial currently underway across 15+ sites in the US, Canada, and Europe. The company collaborates with leading academic institutions and healthcare systems, including Charité, the Mayo Clinic, Duke, and Harvard. At the heart of its work is a clear mission: helping people with heart failure live longer, healthier lives through earlier detection and innovative digital care. The Role: Lead trial start-up including site selection, agreements, and budgets, IRB submissions, site initiation and training Drive enrollment and protocol adherence across sites in close partnership with investigators and site coordinators Own the monitoring strategy and personally conduct monitoring visits, both remote and on-site, in addition to managing any contract monitors Own study budgets, timelines and risk registers, reporting directly to the Chief Medical Officer Run the operational backbone: eTMF, EDC, data cleaning, and protocol deviations Ensure audit and inspection readiness (FDA BIMO, IRB) and maintain sponsor SOPs’ Support the European investigations and regulatory compliance (ISO 14155, MDR) Author and maintain SOPs and work instructions (WIs) for clinical operations, monitoring, and data management Requirements Degree in life sciences, nursing, medicine, biomedical engineering or a related field 5+ years in clinical research, including 3+ years in US FDA-regulated devices Familiarity with SaMD clinical trials Hands-on experience with the full IRB submission lifecycle: preparing and submitting packages, then amending documents like the CIP and ICF as the protocol changes. Hands-on experience taking a US multicenter trial from start-up through enrollment, and closing, on the sponsor side and without a full-service CRO Working knowledge of 21 CFR Parts 812, 50, 56 and 11, ICH-GCP, ISO 14155 and HIPAA; practical experience with EDC and eTMF systems Structured problem-solving and clear prioritization under shifting timelines Strong stakeholder management across academic sites, health systems and senior KOLs Uncompromising on patient safety, data integrity and inspection readiness Fluency in English Authorized to work in the US Nice to have: Cardiology or heart failure trials; pragmatic or health-system-embedded trials App-based or remote monitoring studies (patient onboarding, adherence, technical support) Contribution to a De Novo, 510(k) or PMA clinical evidence package Advanced academic degree (e.g. MSc) Benefits 💵 Competitive pay plus meaningful equity 🫀 Bring a first-in-class digital biomarker through FDA clearance and into routine care 🚀 A dynamic startup with exceptional talent from Harvard, TUM, Meta and Stanford 🌎 Based at our Berlin headquarters with regular visits to US sites and the flexibility to work remotely ✈️ Direct exposure to leading US cardiology centers and the FDA Breakthrough Devices process 🎾 Access to Urban Sports Club to help you stay active and fit

Location: Berlin, Germany The Company: Our client is a digital cardiology start-up headquartered in Berlin and Boston, focused on developing innovative technology to improve outcomes for patients living with heart failure. It has already deployed a CE-marked remote patient monitoring platform across Europe and is now advancing a voice-based Software as a Medical Device designed to detect worsening heart failure through short, daily smartphone recordings. Its voice-based solution has received FDA Breakthrough Device Designation, with its pivotal FDA trial currently underway across 15+ sites in the US, Canada, and Europe. The company collaborates with leading academic institutions and healthcare systems, including Charité, the Mayo Clinic, Duke, and Harvard. At the heart of its work is a clear mission: helping people with heart failure live longer, healthier lives through earlier detection and innovative digital care. The Role: Lead trial start-up including site selection, agreements, and budgets, IRB submissions, site initiation and training Drive enrollment and protocol adherence across sites in close partnership with investigators and site coordinators Own the monitoring strategy and personally conduct monitoring visits, both remote and on-site, in addition to managing any contract monitors Own study budgets, timelines and risk registers, reporting directly to the Chief Medical Officer Run the operational backbone: eTMF, EDC, data cleaning, and protocol deviations Ensure audit and inspection readiness (FDA BIMO, IRB) and maintain sponsor SOPs’ Support the European investigations and regulatory compliance (ISO 14155, MDR) Author and maintain SOPs and work instructions (WIs) for clinical operations, monitoring, and data management Requirements Degree in life sciences, nursing, medicine, biomedical engineering or a related field 5+ years in clinical research, including 3+ years in US FDA-regulated devices Familiarity with SaMD clinical trials Hands-on experience with the full IRB submission lifecycle: preparing and submitting packages, then amending documents like the CIP and ICF as the protocol changes Hands-on experience taking a US multicenter trial from start-up through enrollment, and closing, on the sponsor side and without a full-service CRO Working knowledge of 21 CFR Parts 812, 50, 56 and 11, ICH-GCP, ISO 14155 and HIPAA; practical experience with EDC and eTMF systems Structured problem-solving and clear prioritization under shifting timelines Strong stakeholder management across academic sites, health systems and senior KOLs Uncompromising on patient safety, data integrity and inspection readiness Fluency in English Authorized to travel to the US without Visa restrictions (e.g. ESTA-eligible) Nice to have: Cardiology or heart failure trials; pragmatic or health-system-embedded trials App-based or remote monitoring studies (patient onboarding, adherence, technical support) Contribution to a De Novo, 510(k) or PMA clinical evidence package Advanced academic degree (e.g. MSc) Benefits 💵 Competitive pay plus meaningful equity 🫀 Bring a first-in-class digital biomarker through FDA clearance and into routine care 🚀 A dynamic startup with exceptional talent from Harvard, TUM, Meta and Stanford 🌎 Based at our Berlin headquarters with regular visits to US sites and the flexibility to work remotely ✈️ Direct exposure to leading US cardiology centers and the FDA Breakthrough Devices process 🎾 Access to Urban Sports Club to help you stay active and fit

Location: Canada ClinChoice is a global full-service CRO dedicated to professional development and providing an excellent work-life balance, with a quality-focused, collaborative “one-team” culture. We are looking for a dynamic person to join our in-house team as a Senior Scientist, Risk Management & Safety Surveillance on a permanent basis. Responsibilities Position Summary The scientist will be responsible for core safety deliverables including scheduled and ad hoc aggregate reports and will serve as report owner for assigned reports (medium to large volume, standard complexity). He/She will have in- depth product knowledge and will support Safety Management Team (SMT) deliverables as required. Daily activities involve planning, conducting meetings, database searching, aggregate safety analysis and case level review, writing, and project management/coordination of strategic safety documents. He/She will partner with team members, stakeholders including Medical Safety Officers (MSOs), and a vendor. Primary Responsibilities: •     Ensure timely, quality reports/safety analyses related to core deliverables with oversight as appropriate •     Collaborate with Therapeutic Area Safety Head (TASH), MSO, Safety Surveillance Physician (SSP) and other stakeholders on strategy development •     Initiate, conduct, and oversee searches of internal and external databases •     Perform and/or lead aggregate safety analysis and case level review •     Author, contribute, and coordinate the preparation of core safety deliverables •     Ensure commitments (e.g., Pharmacovigilance Agreements (PVAs) and assessment reports) are met •     Partner with vendor to develop reports/deliverables •     Provide SMT support as needed •     Act as ad hoc member for assigned products as appropriate •     Recognize potential issues and or safety issues and escalate to the attention of    the report owner, line manager, or MSO •     Ability to understand nature of adverse drug reactions and complex associations •     Maintains a high level of flexibility and ability to reprioritize ones work and others •     Attention to detail and ability to analyze data in broader context •     Ability to work across multiple functions and therapeutic areas •     Review regulatory assessor comments/requests and accommodate/address as appropriate with guidance Training/Meetings/Department Initiatives: •     Participate in cross-functional training of relevant stakeholders •     Attend departmental meetings and trainings •     Participate in department and/or cross-functional initiatives Secondary Responsibilities: •     Safety Management Teams (SMT) for assigned products - Lead SMT meeting.  Lead and drive discussions and formulate decisions along with core members •     Risk management plans - Provide guidance on RMP creation and updates.  Reviews and align approvals with oversight leads of the Risk Management plan •     Periodic Benefit Risk Evaluation Report (PBRER)/ Periodic Safety Update Report (PSUR) - Reviews and align approvals with lead oversight.  Leads strategy of the PBRER process. •     Health authority queries -Work with MSO, scientist to organize data, review cases, literature, write Marketing Authorization Holder (MAH) comments •     Participating Affiliate Core Data Sheets (CCDS), US and EU prescribing information updates - Form part of the label working group and provide guidance related to the label updates. •     Signal Validation and Evaluations - Work with Scientist to review preliminary data to determine if the signal is valid and would require further evaluation. Lead and drive the signal evaluation process •     IB updates for safety sections - Evaluate clinical data for ADRs, assist with section 5 and Reference Standard Information (RSI) tables as needed •     DSURs - Reviews and aligns Safety approvals with lead oversight. •     Addendum to Clinical Overviews - Provide support with review, and characterization of risks, data review •     Literature reviews for class effects and ad hoc reports -Review articles and create MAH Comments for assessment of the articles •     Product Safety Strategy (PSS) - Review the risks documented in the PSS and oversee the updates as necessary. Align approval of the PSS updates with oversight. •     Handing Level 2 Escalations/HHE - Participate in level 2 escalations and assess whether there is a Safety impact and an HHE is needed. Lead and drive the HHE process. •     Clinical Development Team (CDT), Local Working Group (LWG) and other cross functional meeting participation - Participate and provide safety inputs as required Minimum Qualifications Education/Experience: ·       Bachelor’s degree in Health or Biomedical Science and six to eight years of industry experience or equivalent, or Advanced degree (preferred) in Health or Biomedical Science and four to six years of industry experience or equivalent) ·       Physician (MD or equivalent) generally requires 2-5 years of pharmacovigilance experience or other relevant experience (e.g., Clinical research, Medical Affairs). Demonstrated skills in clinical medicine with at least 3 years of clinical practice experience is preferred. ·       Clinical/medical writing or pharmacovigilance experience preferred ·       Strong English verbal and written communication skills. ·       Demonstrated knowledge of principles of drug development, assessment of drug risks and benefits, and safety assessment of drugs both on the market and in development as well as global safety regulations, is highly preferred. The Application Process Once you have submitted your CV, you will receive an acknowledgement that we received it. If you have the requirements we need, you will be invited for phone interview as the first step.  Unfortunately, due to the number of applications we receive, we cannot reply to everyone individually if you are not successful. Who will you be working for? About ClinChoice ClinChoice is a global full-service CRO specializing in clinical development and functional solutions for pharmaceutical, biotechnology, medical device, and consumer health companies. We have over 28 years of proven high-quality delivery and results across all our services, with over 4,000 professionals in more than 20 countries across the Americas, Europe, and Asia-Pacific. Our Company Ethos Our mission drives our culture: to contribute to a healthier and safer world by accelerating the development and commercialization of innovative drugs and devices. Our employees are the most valuable company asset and they are  the fulcrum around which all ClinChoice activities are built and close management and training is the core instrument to develop and maintain highly-qualified personnel. The continuous training keeps the resources qualified in terms of competence and expertise and gives all personnel the clear tools needed to manage both internal and client processes with the same methodology.   The success of these core values is evidenced by our below industry average turnover rates. ClinChoice is an equal opportunity employer. We have based our success on attracting, developing, and promoting talent guided by diversity and inclusivity. Our employees come from very diverse backgrounds: gender, race, beliefs, and ethnicities. We recognize this is our strength and celebrate it. #LI-PB1 #LI-Remote AI: Our hiring process includes AI screening for keywords and minimum qualifications. Recruiters review all results. Vacancy: This posting is for an existing vacancy. Open Date: 22-09-2026 Close Date: 06-11-2026 The following disclaimer for CA must be included (remove the equal opportunities wording from the advert template in the bottom paragraph and replace with the following & delete these instructions): ClinChoice Canada Inc. is proud to be an equal opportunity employer, valuing and respecting diversity.  We are committed to inclusive, barrier-free recruitment and selection processes. We will accommodate the needs of qualified applicants under the Human Rights Code and the Accessibility for Ontarians Disabilities Act, in all aspects of the hiring process, upon request by calling + 1 (647)724-5709 x 301. We thank all applicants for their interest; however, only those being considered for an interview will be contacted. In accordance with Federal Personal Information Protection and Electronic Documents Act ("PIPEDA") , personal information is collected under the authority of the Act and will only be used for candidate selection. The base salary pay range represents the anticipated low and high range for this position. Actual salary will vary based on various factors such as the candidate’s qualifications, skills, competencies, and proficiency for the role. Canada Pay Range $80 — $115 CAD

Location: Remote Workplace: Remote Our Team Dandelion Health unlocks a layer of unexplored clinical depth that has been previously inaccessible at scale. By combining all the raw multimodal data from community health systems with validated AI models, we deliver regulatory-grade scientific insights and products that give teams the evidence to design better trials, enroll the right patients, and generate AI-powered insights that drive confident decisions across the development and commercial lifecycle. Your Role You are a healthcare data scientist who knows your way around clinical and electronic health record data. Your primary responsibility is to partner collaboratively with our clients to develop data science solutions and analyze AI-ready datasets to provide key insights using multimodal data. You will curate datasets by identifying patient subpopulations or disease cohorts, and pool multimodal data to drive rapid exploratory AI/ML and Real-World Evidence analyses, model experimentation, and/or model validation. You will lead analytics research from inception to closeout by having ownership over study design, data curation strategies, effort estimation, analytic design, and delivery of final results. You will use your data expertise, programming abilities, and critical thinking skills to support our clients by designing and delivering solutions to help them tackle a broad range of business challenges. Your team’s ultimate goal is to deliver the highest-quality data possible to our clients, who are building products that improve patient health, and demonstrate the value of these data. You will report to the Research Data Science Manager.   Responsibilities Your day-to-day responsibilities will include the following: - Collaborate with clients to develop creative analytic solutions that create value and address challenges across critical areas of their business. - Design statistical analysis plans for evidence generation projects that include methodology, results structure, expected outputs and dataset requirements; - Query complex source systems in a range of health data sources (e.g., EMRs, ECG data, DICOM data) to identify and map data elements in order to create high-quality datasets for analytic and AI use cases; - Develop descriptive analyses and in-depth predictive and causal inference models to drive evidence generation on Dandelion data and enhance existing data products; - Summarize the methods and results from projects into clear explanations and documentation for internal and external audiences including for submission to conferences and peer-reviewed publications; - Support all phases of SQL/analytical programming, data management, quality control, and reporting for analytics projects; - Develop code and documentation to deliver high-quality and HIPAA-compliant data products on time to internal and external customers; - Create summarized findings and recommendations that are clearly presented and adapted for audiences that have a varying range of technical and clinical experience; - Identify and resolve problems using your knowledge, background, and troubleshooting skills; - Ensure accuracy, data integrity, and validity of data and analysis in all work; - Present to senior leadership as well external audiences You are not afraid to dig into massive, confusing, disorganized new datasets and get them under control. You are excited to learn new environments, languages, and skills. This is a small, early stage company with enormous ambitions and everyone pitches in across the team.   Qualifications - M.S. or PhD degree in a relevant field, such as Biomedical Informatics, Data Science, Biostatistics, or B.S. with at least seven years of experience - Experience in client interaction, crafting project proposals, and leading teams. - Background in statistical modeling and real-world data analysis - Fluency in Python and SQL - 1+ years experience with extracting, curating, and analyzing data created within the HIT and healthcare delivery ecosystem (e.g., EMR, claims, registry); this may include knowledge of the roles of data exchange and content standards (e.g., FHIR, CDA, CQL) and clinical terminology standards (e.g., ICD, CPT, LOINC, SNOMED-CT, NDC, RxNorm) - Strong technical writing, editing, and communication skills along with a collaborative, client-first mindset - Excellent organizational skills with an ability to embrace change and effectively manage multiple projects and consistently plan work to meet deadlines - Experience working in or with startups is a plus Technology Experiences and Skills   We don’t expect anyone to have all of the following skills or experiences, but we do seek candidates who are interested in growing their skill sets and working with healthcare data in all its glorious complexity. The Data Team works closely with our Engineering Team to put our work into production and meet client needs. - SQL - Python and/or R - Git and version control - Familiarity with encryption methods and writing regular expressions - Prior experience querying EDWs or databases and creating reports or analytics for healthcare data - Familiarity with the data aspects of electronic medical records, ex. Epic, Cerner, Allscripts - Prior experience working with insurance claims data - Familiarity with medical terminologies or controlled vocabularies such as ICD-10, SNOMED-CT, LOINC, CPT/HCPCS, NDC, and RxNorm - Any medical ontology experience - Any NLP experience - Any experience working with DICOM or other imaging modalities - Experience with OMOP common data model - Familiarity with Machine Learning concepts - Experience with AWS Note that familiarity with machine learning model development and deployment is not required for this position, but familiarity with high-level ML concepts is a plus. Nature of our work   Our work is fast paced and iterative. We are growing, and we want to support our team members to grow in their skills as well. We are building a team that approaches problems with a diversity of perspectives, values experimentation, and refining our approach based on that experimentation. We work with the full spectrum of healthcare data from tabular data, videos, images, waveforms, etc. If a health system collects it, we might work with it! If this looks like a partial fit, please reach out, we would love to share more about the work we do for you to understand if it would be a good fit for you. There is occasional travel for in-person company working days on roughly a quarterly basis. Team Benefits - Remote work and flexible hours. Availability needed for meetings, which we try to keep to a healthy minimum - Complete wellness benefits including healthcare, dental, vision, PTO, sick days and more. Ask for details - Professional development days to build your skills - Collegial work environment - Academic bent towards inquiry and problem solving but start-up speed and flexibility - Great balance of focus time to work on projects but easy to access team members to discuss issues and work collaboratively - Dandelion is a mission-driven company that is focused on improving patient care

Location: Remote Workplace: Remote Our Team Dandelion Health unlocks a layer of unexplored clinical depth that has been previously inaccessible at scale. By combining all the raw multimodal data from community health systems with validated AI models, we deliver regulatory-grade scientific insights and products that give teams the evidence to design better trials, enroll the right patients, and generate AI-powered insights that drive confident decisions across the development and commercial lifecycle. Your Role You are a healthcare data scientist who knows your way around clinical and text-based data. Your primary responsibility will be to leverage and build upon large language models (LLM) and other ML-based approaches for meaningful data abstraction from both unstructured and structured healthcare data. You will join a team of data scientists who own the creation and maintenance of AI-ready datasets for clients in our environment. You will work across the organization to curate datasets by identifying patient subpopulations or disease cohorts, developing methodology to abstract information from multimodal healthcare data sources to support patient phenotyping, and pooling data to enable rapid exploratory AI/ML analyses, model experimentation and/or model validation. You will use your data expertise, programming abilities, and critical thinking skills to support our technical product team, and develop your own analyses to derive insights and enhance our datasets based on the use case. Your team’s ultimate goal is to deliver the highest-quality data possible to our clients, who are building products that improve patient health. You will report to the Data Science Manager, under the Head of Data.   Responsibilities Your day-to-day responsibilities will include the following: - Develop Natural Language Processing (NLP), Large Language Model (LLM) and other ML-based pipelines to abstract relevant labels from text-based healthcare data and store them in scalable data models; - Query complex source systems in a range of health data sources (e.g., EMRs, semi-structured reports, free-text clinical provider notes) to identify key data elements and create and enrich high-quality datasets for real-world evidence analyses and training AI algorithms; - Own data extraction, wrangling, labeling and QC tasks to create analytical datasets that include abstracted clinical concepts and provide a range of solutions to support customers’ AI activities; - Stay current on the latest in applied NLP and generative AI methods and proactively leverage these technologies where applicable; - Support the design, testing, validation, analysis, and merging of multimodal data structures from a wide variety of source systems; - Develop code and documentation to deliver high-quality and HIPAA-compliant data products on time to customers; - Identify and resolve problems using your knowledge, background, and troubleshooting skills; - Ensure accuracy, data integrity, and validity of data and analysis in all work; - Provide support for technical product team to advance development of the suite of data-related product offerings; - Summarize the complexity of abstraction methods, findings and recommendations into clear explanations and presentations for internal and external audiences that have a varying range of technical and clinical experience; You are not afraid to dig into massive, confusing, disorganized new datasets and get them under control. You are excited to learn new environments, languages, and skills. This is a small, early stage company with enormous ambitions and everyone pitches in across the team.   Qualifications - Advanced degree in a quantitative field (ex. Data Science, Biomedical Informatics, Computer Science, Biostatistics), or B.S. with at least 5 years of professional experience - At least 2 years of data science and machine learning experience, including building pipelines to extract and curate unstructured and semi-structured data by applying advanced machine learning and AI techniques. Prior experience with clinical and healthcare data is a strong bonus. - Fluency in Python and SQL, including fluency with ML/NLP libraries (PyTorch, Tensorflow, HuggingFace, etc.) - Familiarity with using modern applied LLM techniques on real-world data - Strong technical writing, editing, and communication skills, along with a collaborative mindset - Excellent organizational skills with an ability to embrace change and effectively manage multiple projects and consistently plan work to meet deadlines - Experience working in or with startups is a plus Technical Experiences and Skills   We don’t expect anyone to have all of the following skills or experiences, but we do seek candidates who are interested in growing their skill sets and working with healthcare data in all its glorious complexity. The Data Team works closely with our Engineering Team to put our work into production and meet client needs. - Git and version control - Familiarity with encryption methods - Prior experience querying EDWs or databases and creating reports or analytics for healthcare data - Familiarity with the data aspects of electronic medical records, ex. Epic, Cerner, Allscripts - Any medical ontology experience - Any experience working with DICOM or other imaging modalities - Experience with AWS - Experience with publishing work in peer-reviewed journals Nature of our work   Our work is fast paced and iterative. We are growing, and we want to support our team members to grow in their skills as well. We are building a team that approaches problems with a diversity of perspectives, values experimentation, and refining our approach based on that experimentation. We work with the full spectrum of healthcare data from tabular data, videos, images, waveforms, etc. If a health system collects it, we might work with it! If this looks like a partial fit, please reach out, we would love to share more about the work we do for you to understand if it would be a good fit for you. There is occasional travel for in-person company working days on roughly a quarterly basis. Team Benefits - Remote work and flexible hours. Availability needed for meetings, which we try to keep to a healthy minimum - Complete wellness benefits including healthcare, dental, vision, PTO, sick days and more. Ask for details - Professional development days to build your skills - Collegial work environment - Academic bent towards inquiry and problem solving but start-up speed and flexibility - Great balance of focus time to work on projects but easy to access team members to discuss issues and work collaboratively - Dandelion is a mission-driven company that is focused on improving patient care