Data Scientist вакансии - гибрид

Responsibilities: • Conduct group sessions on AI, Data Science, ML models • Answer student questions and provide support The school teaches in Kazakh and is the first AI and Big Data school in Central Asia.

Задачи: - разрабатывать и улучшать алгоритмы обнаружения фрода; - создавать и дорабатывать эвристики и ML-модели; - работать с задачами классификации текстов: экспериментировать с разными архитектурами и таргетами; - подготавливать, размечать и анализировать данные; - оценивать качество моделей и отслеживать их поведение в продакшене; - анализировать эффективность решений на данных и бизнес-метриках; - участвовать во внедрении ML-решений. Требования: - базовые знания в ML / Data Science и знакомство с задачами NLP; - умение работать с данными и писать на Python (Pandas, NumPy), знакомство с Jupyter Notebook; - владение SQL для извлечения данных; - понимание основных ML-методов и их применимости; - готовность учиться, работать в команде и принимать обратную связь; - чтение технических материалов на английском языке; - готовность к работе с большим объёмом устной коммуникации.

Location: New York, NY (HQ); San Francisco, CA; Remote (US) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE We’re looking for someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. WHAT YOU’LL DO - Full stack development, building models to consume, transform, and expose data to stakeholders and production systems - Drive a culture of experimental design, testing agenda, and best practices - Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way - Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success - Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action WHAT YOU NEED - Minimum of 4 years of industry experience as a Data Scientist - Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries - Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards - Track record of shipping high quality products and features at scale - Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions NICE-TO-HAVES - Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents) - Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development) - Experience within the payments and financial technology space - Familiarity with B2B enterprise sales cycle metrics and processes ABOUT OUR TEAMS - Product Data | Ramp’s Product Data team is responsible for delivering data products and insights that shape Ramp’s product direction and unlock business value. The Product Analytics team is also responsible for building out the platform through which new products are launched, instrumented, tested, and QA’d. The team embeds deeply as a partner to engineering, product, and design. - Risk & Capital Markets Data | Ramp’s Risk Data team is responsible for how risk is evaluated, and building the risk infrastructure to scale to millions of businesses in the United States. Areas include risk operations and underwriting, limit setting and pricing across financial products as well as fraud detection, regulatory reporting, and capital market relationships. - Growth Data | Ramp's Growth Data team ships data products and insights that allow Ramp to acquire new business and expand existing business and partnerships at scale. Current areas of focus include: Web & Martech, Outbound Automation, Customer Data Platform, Self-Service Product, GTM Strategic Finance, and Business Systems. BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

О ПРОЕКТЕ Команда занимается развитием внутренней AI/ML-платформы, AutoML, разработкой LLM/NLP-решений, мониторингом качества моделей на крупном финтех-проекте. ПРЕДСТОЯЩИЕ ЗАДАЧИ • Разработка и развитие ML/LLM-сценариев для production; • Работа с AutoML, NLP и RAG-пайплайнами; • Оптимизация качества и стабильности ML-решений; • Интеграция с MLOps/DE-инфраструктурой; • Быстрое прототипирование и проектирование AI-решений. ОЖИДАНИЯ ОТ КАНДИДАТА • 3+ лет опыта в DS/ML; • Хороший Python и уверенный ML-стек (Sklearn, CatBoost/LightGBM/XGBoost, Pandas, NumPy), опыт с табличными данными; • Опыт с LLM/NLP (для проекта в данном направлении); • Опыт работы с Spark/Hadoop/Hive; • Понимание production ML-процессов. БУДЕТ ПЛЮСОМ • PyTorch / DL; • Open-source contribution; • Full-stack опыт. УСЛОВИЯ РАБОТЫ • Оформление по ТК или ИП в аккредитованную ИТ-компанию; • Сильная инженерная команда и обмен экспертизой; • Гибридный или удаленный формат работы (РФ!); • ДМС со стоматологией с 1-го дня; • Предоставление техники (на выбор, по запросу).

Location: Limassol; Nicosia Workplace: hybrid The Role:  We are looking for an experienced Data Scientist to join our Data Science department. In this role, you will work hands-on on advanced analytics and machine learning projects, leveraging large datasets to build impactful, production-ready solutions.  Ideal for someone who enjoys solving complex problems, building models end-to-end, and driving data-driven decision-making The main responsibilities of the position include: Design, develop, and review machine learning models and advanced analytics solutions Apply statistical analysis and data mining techniques to extract meaningful insights from large datasets Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality Collaborate with cross-functional teams including data engineers, software engineers, product owners, and business stakeholders Present insights, analysis results, and recommendations to both technical and non-technical audiences Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics Contribute to the development of the department’s data science strategy and identify opportunities where data science can deliver business value Main requirements: University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field At least 3 years of experience in data science, machine learning, or advanced analytics Strong programming skills in Python and experience with Pandas, NumPy, and similar data analysis libraries Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly Strong knowledge and exposure to Machine Learning Knowledge of Recommendation Systems will be considered a plus Solid understanding of statistics and data mining techniques Experience working with relational and non-relational databases Strong analytical thinking, problem-solving ability, and attention to detail Excellent communication skills and the ability to work collaboratively in a team environment Benefit from: Attractive remuneration package Private health insurance Corporate pension fund Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Bring It to Life – Role-Specific Take-Home Task Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Location: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE Replit spreads through companies differently than it does through individuals. One person builds an app, colleagues start using it, a team forms, an admin rolls Replit out more widely, and eventually Sales gets involved. You'll be the data scientist for Replit's enterprise business, covering both the product and the go-to-market motion: how Replit spreads inside organizations, what keeps teams engaged after rollout, which features and signals drive expansion, and how all of that becomes pipeline, revenue, and a reliable forecast. Experimentation is hard here. There are far fewer accounts than users, people within an organization influence each other, and admins control what their teams see. You'll figure out how to learn quickly and rigorously anyway. You'll work with Enterprise Product, Engineering, Sales, Customer Success, RevOps, and Finance, and your work succeeds when it changes a product, GTM, or investment decision. YOU WILL: - Define how we measure the enterprise business end to end: account-level activation, breadth (share of seats active), depth (apps built, deployed, and shared), collaboration, consumption, and net revenue retention - Understand virality inside organizations: how Replit spreads from a first builder to teams through app sharing, invites, and viewers who become builders; quantify within-account network effects and find the levers that accelerate them - Explain post-engagement churn: why seats and accounts that engaged at rollout go dormant, separate seat-level decay from account-level risk, and turn it into account health models that give the product and Customer Success early warning and a clear next action - Identify the product behaviors and features that precede seat expansion and plan upgrades, and use them to build product-qualified account (PQA) models that route bottoms-up usage to Sales at the right moment - Measure adoption and value for enterprise features — admin and governance controls, security, data connectors, collaboration, and deploying to data platforms — and use it to inform what we build next - Design experiments for enterprise: account- and cluster-level randomization, interference within organizations, small samples and heavy-tailed account sizes, stratified and matched-pair designs, staged rollouts and long-running holdouts, synthetic control, and Bayesian or hierarchical models where data is sparse - Measure the incremental impact of GTM programs — pilots, onboarding, enablement, and sales-assist — with the same rigor as product launches - Own enterprise forecasting for pipeline, bookings, consumption, and expansion, and pressure-test the assumptions behind capacity and quota plans - Analyze pricing and packaging: seats vs. consumption, and how contract structure shapes usage - Build a trusted enterprise data layer that joins product telemetry, CRM, and billing data and models the org, workspace, team, and seat hierarchy, so Product, Sales, and leadership can self-serve — increasingly through AI agents rather than static dashboards - Bring a point of view to the enterprise roadmap and GTM strategy before you're asked REQUIRED SKILLS AND EXPERIENCE - 6+ years in product or GTM data science, with significant experience on B2B, collaboration, or multi-seat products - Hands-on experimentation where the unit of randomization differs from the unit of analysis: cluster randomization, interference, and small-sample designs - Strong retention and survival modeling, cohort analysis, and segmentation at both user and account level - Experience defining adoption, retention, and revenue metrics (activation, NRR, GRR, expansion) and getting the company to agree on them - Built scoring or forecasting models that Sales, Customer Success, or Finance actually used - Expert SQL, including messy CRM, billing, and product data joined at the account level; strong Python; comfortable building your own datasets in dbt - A track record of analysis that changed a product roadmap or GTM decision, and the confidence to push back on an attractive story when the evidence doesn't support it - Heavy, practical use of AI tools to move faster in your own work PREFERRED QUALIFICATIONS - Experience at a company that grew from bottoms-up adoption into enterprise sales (collaboration, productivity, or developer tools) - Consumption- or usage-based revenue models and PLG-to-sales motions (PQLs/PQAs, sales-assist) - Virality, network, or graph analysis of collaboration data - Fluency with Salesforce data and RevOps tooling - Modern data stack: BigQuery, dbt, Hex BONUS POINTS - Experience with enterprise admin, security, or governance product surfaces - Built AI agents for GTM teams (account research, deal reviews, QBR prep) - Early member of an enterprise or GTM data function This is a full-time role based in our Foster City, CA office with an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: Toronto; San Francisco; Canada; Seattle; London; United States; New York Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Evaluation is critical to making progress in scaling intelligence. As models continue to become superhuman in many real-world use cases, we must continue to develop new evaluation techniques that accurately reflect what models are already capable of, as well as set the agenda for what future models should be capable of. In this role, you are responsible for creating these next-generation evaluation methods and infrastructure to measure LLM progress. Key Responsibilities: - Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish. - Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations. - Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency. - Build scalable and reusable tools for digging into model performance. Qualifications: - You enjoy rapidly building prototypes that demonstrate the boundaries of what LLMs are capable of, and you have developed resources to measure those capabilities. - You have spent dozens of hours reviewing complex data and LLM outputs to ensure high data quality. - You are obsessive about rigorously measuring AI capabilities, and also about making sure your measurements actually align with the capabilities you care about. - You have strong software engineering skills. Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry. Within the Data team, you’ll join the BI/Prediction Team which is an autonomous squad of around 10 people. The team is composed of top-tier product managers, software & data engineers, data scientists and data analysts. ROLE The objective of this team is to accelerate the growth of the company by serving as the on-demand prediction provider for all Voodoo BUs. This involves addressing critical needs such as predicting campaign LTV for User Acquisition optimization, determining optimal monetization offers for millions of players or constructing confidence intervals for time series data prediction. We want to onboard a passionate senior data scientist with significant experience in a similar environment to allow us to go one step further. This is an opportunity to have a strategic and critical impact on Voodoo’s success. This position is hybrid and requires 3 days per week in the office based in Paris. - Take ownership of our products modeling pipelines - Contribute to high modeling performance through insightful ideas and initiatives. - Build and deploy quickly scalable ML systems. - Engage with colleagues across the company to leverage new ideas and perspectives and demonstrate excellent communication to efficiently cooperate with product managers, teammates and stakeholders. - Deep dive into data to discover relevant insights. - Build a rich understanding of the mobile gaming industry, the company strategy, our products and their fit within the company’s daily operations. - Mentor and guide a team of data scientists, fostering technical excellence and autonomy. - Establish and enforce best practices in ML engineering, experimentation, and reproducibility across projects. - Champion a culture of impact-driven research, ensuring models not only perform well technically but also create tangible business value. - Proactively identify risks in modeling approaches, data quality, scalability, business alignment and design mitigation strategies. PROFILE - Extensive experience building machine learning systems - Extensive experience with Python, SQL and MLOps best practices - Cloud experience needed (ideally AWS but could be another cloud provider) - Airflow and DBT experience is a nice to have - Excellent Communication in English and French mandatory - You enjoy working in a team, learning new things, sharing knowledge - Experience in a tech startup/scaleup is a plus - Strong achievements on Kaggle will be valued BENEFITS - Competitive salary - Comprehensive relocation package (including visa support) - Premium healthcare (SideCare) for you and your family 100% borne by Voodoo - Swile Lunch voucher - Gymlib (100% borne by Voodoo) - Wellness activities in our Paris office - Unlimited vacation policy - Remote days - Child daycare facilities (Les Petits Chaperons rouges)