Вакансии

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Tick Data Platform is a new team building a globally distributed market data architecture. The systems are being developed from the ground up and we’re looking for exceptional software engineers to join us in creating scalable and performant data platforms to support quantitative research and trading. Your future role within QRT: Greenfield development in a small and highly collaborative team Building cloud-native platforms for the distribution and processing of realtime tick data Architecting high throughput distributed systems with significant horizontal scalability Working with researchers and data scientists across QRT Your present skillset: 4 years of software engineering experience Experience with distributed realtime systems Systems design and architecture Ability to write optimised and high throughput code Communication and teamwork, with an interest in building a strong engineering culture Experience in these is advantageous but not required: Cloud-native platforms including Kubernetes Realtime platforms including Kafka High performance python tooling (numpy, numba, c++ and rust interoperability) Modern data tooling (polars, arrow, flight/grpc) C++ or Rust Market data SRE and DevOps Project leadership and stakeholder management QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Paris; London Workplace: Hybrid TL;DR: We're looking for a Data Labeling Lead to build our annotation team from zero – setting quality standards, designing evaluation frameworks, and running the labeling operations behind our safety evals, RLHF, and benchmarks. You'll own quality, throughput, and cost while working side by side with our AI researchers. ABOUT US White Circle http://whitecircle.com is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale. - We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others - We process over 100M+ API calls every month - We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We’re at a multi-million dollar run rate already having signed customers like Lovable and multiple neobanks. You’ll be joining at the most exciting time - early enough that the equity can be life-changing, but at a point where demand has been proven. IN THIS ROLE, YOU WILL - Build from scratch and lead the Data Labeling team (hiring, coaching, and performance management) - Define annotation guidelines, quality standards, and evaluation frameworks - Develop quality assurance processes, calibration sessions, and auditing systems - Partner with AI researchers and engineers to translate research objectives into labeling workflows - Prioritise labeling projects based on business and research needs - Monitor operational metrics including quality, consistency, throughput, and cost - Improve annotation tooling, automation, and workflow efficiency - Lead complex AI evaluation projects, including safety, preference ranking, RLHF, policy evaluation, and benchmark creation - Analyse disagreement patterns and edge cases to improve guidelines and model performance - Manage vendor relationships and ensure consistent quality across distributed teams - Build reporting dashboards and communicate operational insights to leadership - Foster a culture of continuous improvement, accountability, and operational excellence WE'RE LOOKING FOR SOMEONE WHO - Has experience leading data annotation or AI evaluation teams - Has strong operational and people management skills - Understands AI model evaluation, LLM behaviour, and modern annotation workflows - Can design scalable processes without sacrificing quality - Communicates clearly across technical and non-technical teams - Thrives in fast-moving startup environments YOU MIGHT BE A GREAT FIT IF YOU - Have managed annotation programs for LLMs, generative AI, or machine learning - Have experience with RLHF, preference data collection, safety evaluations, or benchmark creation - Have worked in Trust & Safety, AI Safety, Content Moderation, or ML Ops - Have managed distributed or global annotation teams - Have experience with vendor management and outsourcing operations BONUS POINTS - Familiarity with prompt engineering and AI safety policies - SQL, Python, or data analysis experience - Experience building internal annotation platforms or workflow automation - Background in linguistics, cognitive science, machine learning, or data operations Important note This role involves overseeing projects that may include offensive, harmful, violent, sexual, or otherwise disturbing content. You'll be responsible for ensuring reviewers have the tools, guidance, and support necessary to perform this work safely and consistently. COMPENSATION & BENEFITS - Competitive compensation, including equity - Flexible time off - A spacious office in the heart of Paris’s 2nd arrondissement, with a flexible hybrid setup - Relocation support if you’re moving to Paris, available after your probationary period - Premium private health insurance - Mental health support, including coverage for therapy when you need it - Language lessons to help you improve your English or French - Lunch and dinner covered when you work from the office - Learning and development support for courses, conferences, and opportunities to grow your skills - All the hardware, subscriptions, tools, and services you need - Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella PROCESS 1. Intro call (25 min) 2. Take-home test assignment 3. Final conversation with CEO (45 min) Please submit your application in English.

Location: Argentina Brainlabs is the independent, founder-led agency building the future of media. We have over 1000 Brainlabbers based across the global, all united through the 12 principles laid out in our Culture Code. We're full-service, with people and AI agents working side by side, all aligned to one thing: maximizing our clients' revenue through a genuinely scientific approach to media. If you want to help play your part in achieving this for the world's biggest brands in an environment that will support and challenge you in equal measure, this is where you do it. Tell me about this role! As a Manager, SEO & Data Analytics , you will help shape how we define, measure, and report performance across a single enterprise SEO program. You will turn complex search, AI visibility, keyword, and reporting requirements into clear methodologies that client teams can use with confidence. This role sits at the intersection of SEO strategy, data analysis, and stakeholder reporting, helping ensure our measurement approach is consistent, actionable, and aligned to client business goals. What you do Define reporting requirements, measurement frameworks, and governance standards across SEO and AI Search workstreams for a single enterprise client. Build durable approaches for keyword coverage, AI visibility tracking, prompt categorization, reporting cadence, and KPI interpretation. Partner closely with SEO, data, and client delivery teams to turn ambiguous asks into structured requirements. Identify reporting risks or gaps and ensure insights are clear enough to support executive-level decision-making. Who you are Strong enterprise SEO, B2B SaaS, measurement, and reporting experience Comfortable working with imperfect or evolving data, with the ability to create structure, rigor, and consistency BigQuery and Adobe Analytics experience Strong data analysis skills with the ability to translate technical details into clear business implications Highly organized, detail-oriented, and confident working across SEO, analytics, and client stakeholders How you succeed You will live our culture code every day! Effective campaign creation and delivery metrics. Internal targets/metrics on technology adoption and process optimisation met. You will hit our quality assurance metrics on all campaigns you lead. Client satisfaction targets being met (internal & external). Learning certifications created and met across the practice. Actively managing workload of your delivery teams to maximize output. What's in it for you ✨ This is a full time role (en relación de dependencia) Hybrid salary (50% of your net salary in USD) 20 working days vacation plus all Argentina public holidays. Private healthcare (OSDE 360). Adaptive/hybrid working. Free breakfast and lunch when in office. Access to learning and development opportunities. Mobility programmes - work from another country for up to 30 days! #LI-CO1 What happens next? We know searching for a job is tough and that you want to find the best career and employer for you. We also want to ensure that this position is the best fit for both you and us. Therefore, you will participate in a comprehensive interview process that includes skills interviews with our team. The goal of this process is to allow you to get to know us as we learn more about you. A note on our offices: We pride ourselves in being a company with an office-centric culture and, for the majority of roles we expect people to be in commuting distance of the office and come in for around 3 days per week. Brainlabs actively seeks and encourages applications from candidates with diverse backgrounds and identities. We are proud to be an equal opportunity workplace: we are committed to equal opportunity for all applicants and employees regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion, or belief, and marriage and civil partnerships. If you have a disability or special need that requires accommodation during the application process, please let us know! For details regarding our data processing activities, please refer to our Candidate Privacy Notice Protect Yourself from Job Scams: We've been made aware of fraudulent job offers circulating in Brainlabs' name. Your safety is our priority, so please stay vigilant. Brainlabs will never ask you to transfer money, pay for a job opportunity, or request sensitive information such as Social Security numbers, banking details, or passwords via email, WhatsApp, or unsecured channels. Our official hiring communications only come from verified email domains (@brainlabsdigital.com, @brainlabs.ai, @exverus.com, @jacknimble.com.au, @sparro.com.au) and trusted platforms including Greenhouse, Upwork, Yuno Juno, and Remote. If you receive a suspicious message claiming to be from Brainlabs, do not engage. Instead, forward it immediately to security@brainlabsdigital.com . We're committed to protecting our community and ensuring a safe candidate experience. Thank you for your vigilance.

Location: Paris Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT: As part of the Data Search & Analytics team, you will support one of QRT's Options trading streams, working closely with quantitative researchers and traders to source, curate and deliver high-quality data that powers systematic options research and trading. In addition to the core responsibilities outlined above, you will: Source, evaluate and onboard datasets relevant to options and derivatives research. Partner closely with researchers and traders to understand data requirements and translate them into scalable data solutions. Build and maintain robust data pipelines, ensuring the quality, consistency and timeliness of options-related datasets. Develop a strong understanding of options market data and contribute to improving QRT's internal data platform and tooling. Proactively identify opportunities to enhance data coverage, quality and operational efficiency for the Options business. Your present skillset: 3+ years of experience as a Data Scientist, Data Engineer or in a similar data-focused role; experience supporting quantitative research or trading teams is advantageous. Experience working with financial market data; exposure to options, derivatives or volatility data is a strong advantage. Strong Python programming skills, with experience using data processing libraries such as Pandas and NumPy. Experience building data pipelines and working with large-scale structured and time-series datasets. Demonstrated interest in financial markets and the application of data to quantitative research and trading. Excellent communication and stakeholder management skills, with the ability to collaborate effectively with researchers, traders, engineers and external data vendors. Ability to thrive in a fast-paced, high-performance environment while managing multiple data initiatives simultaneously. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. The Tick Data Platform team is a new team building a market data architecture for low latency trading. The systems are being developed from the ground up and we’re looking for exceptional software engineers to join us in creating scalable and performant tick data platforms to support HFT. Your future role within QRT Greenfield development in a small and highly collaborative team Writing modern high-performance C++23 Architectural contributions to newly designed systems Adding new exchanges to the platform Project leadership Working with developers and researchers across the low latency teams at QRT Your present skillset: 4 years of experience writing low latency / high-performance modern C++ Experience with market data is highly desirable Familiar with C++ optimisation techniques Linux internals, kernel bypass and low-level profiling / tuning Communication and teamwork, with an interest in building a strong engineering culture Nice to have: System design and architecture Scripting in Bash or Python Project leadership and stakeholder management QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Mumbai Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. In this role, you will be involved managing data operations activities to onboard, maintain, and support new datasets within QRT. You will also be responsible for production monitoring and ensuring the smooth functioning of data pipelines and infrastructure systems. Your future role within QRT Own and automate data operations processes, including coordination with external vendors and internal data teams Enhance observability of data pipelines by creating and maintaining dashboards and implementing automated checks Monitor data pipelines and provide Level 1 production support Monitor framework and infrastructure systems to ensure operational stability Maintain and update operational runbooks and process documentation Your present skillset Bachelor’s or master's degree in engineering or a related field. 3+ years of Experience in data operations and production support Strong Python scripting skills Collaborative mindset with a positive and proactive attitude Strong problem-solving skills, communication abilities, and attention to detail QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. You will work within a data focused function supporting Quantitative Researchers, Traders and other stakeholders across the firm. The role focuses on designing and developing financial datasets that support systematic strategies and trading decisions, with particular emphasis on market data, pricing datasets and reference data. You will combine financial market knowledge with Python and data engineering skills to build and own the automated production pipelines that create and maintain these datasets. Your future role within QRT Collaborate with Quantitative Researchers and Traders to design financial datasets that support systematic strategies and trading decisions Develop Python code to extract, clean, normalise and aggregate data from a range of financial market data sources Design, build and maintain automated data pipelines covering sourcing, extraction, transformation, validation and delivery Develop and maintain pricing and reference datasets across financial instruments and markets Investigate and resolve data quality and production issues to improve the reliability and availability of datasets Evaluate and implement new approaches to data extraction, processing and onboarding Take ownership of production data workflows and evolve them as data requirements, systems and business priorities change Your present skillset 2 to 5 years of experience in a data focused role working with financial or market data Strong understanding of financial markets and instruments, including the behaviour and characteristics of pricing and reference datasets Advanced Python programming skills, including experience with data processing libraries such as Pandas or Polars Experience designing, building and maintaining automated production data pipelines Strong data analysis and problem solving skills, with the ability to investigate data quality issues and understand their underlying causes Experience working with market data platforms and APIs from providers such as Bloomberg or LSEG is beneficial, including products such as Datastream, DataScope Select, Real Time, BPIPE or Data License Postgraduate degree in Mathematics, Physics, Engineering, Computer Science or another quantitative discipline Strong communication skills with the ability to collaborate effectively with Quantitative Researchers, Traders and other stakeholders Ability to operate effectively as priorities, systems, projects and business requirements evolve QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Sydney Software Engineer – Core - Data & Lifecycle Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating across all liquid asset classes worldwide. We are a technology and data-driven organisation applying a scientific approach to investing. By combining data, research, technology, and trading expertise, we tackle complex problems in a highly collaborative environment. Our culture of innovation underpins our ambition to deliver high-quality returns for our investors. Your role at QRT We are looking for a Software Engineer to join our Core Data & Lifecycle Engineering team in Sydney. This team builds and owns critical systems that sit at the heart of QRT’s trading operations—powering trade and position lifecycle management, reference data, and reporting workflows across all asset classes. These systems are highly visible and directly influence trading decisions, risk management, and operational efficiency. This is primarily a hands-on engineering role (≈80% development), with a smaller component (≈20% support and system ownership) focused on maintaining robustness, reliability, and data quality in production. You’ll work closely with trading, research, risk, and operations teams, gaining strong exposure to the business while building scalable, high-performance systems. What you’ll work on Designing and building scalable, high-performance systems for trade and position lifecycle management Developing solutions to automate lifecycle events such as corporate actions, expiries, and cash flows across asset classes Building and maintaining high-quality reference data platforms used across trading and research Delivering real-time and end-of-day reporting pipelines for internal and external stakeholders Ensuring data accuracy, integrity, and consistency across systems and workflows Contributing to system validation, controls, and operational robustness, including alignment with brokers and fund administrators Collaborating closely with stakeholders to translate business needs into reliable technical solutions Writing well-tested, maintainable code and contributing to CI/CD and deployment pipelines Supporting production systems and continuously improving reliability, monitoring, and performance What we’re looking for 5–10 years of software engineering experience, ideally in a high-performance or data-intensive environment Strong programming skills in Python (experience with C# is a plus) Solid understanding of software design, architecture, and scalable systems Experience working with SQL and relational databases Familiarity with testing frameworks and CI/CD practices Domain experience (one or more is valuable, not required) We’re interested in engineers with exposure to financial markets, particularly: Trade and position lifecycle systems Equities, ETFs, futures, or options Corporate actions and reference data Market structure and exchange-specific behaviour Deep expertise in a single asset class is not required—but an interest in learning and working in a trading environment is important. What will set you apart Experience building systems in a quantitative trading or financial environment Strong problem-solving skills with a focus on performance, scalability, and data quality Ability to operate in a high-impact, fast-paced environment with evolving requirements Clear communication skills and a collaborative mindset Why join QRT? Work on business-critical systems with direct impact on trading outcomes Join a core engineering team with significant ownership and autonomy Collaborate with traders, researchers, and engineers in a highly technical environment Tackle complex data and systems challenges at scale

Location: New York Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT This team is integral to the firm’s success. We are seeking a technically skilled Data Support Engineer to support quantitative researchers and traders in navigating and using extensive datasets. You will support all data users, contribute to documentation, and ensure data quality. Provide first-line support to researchers and traders for data access ad usage. Collaborate with data engineers to resolve data issues. Onboard new hires and train them on using data tools and processes efficiently. Manage JIRA workflows, track support requests, and ensure timely resolution of data issues. Contribute to data documentation. Contribute to extending data coverage (live collection and backfills) Your present skillset A bachelor’s degree in Data Science, Computer Science, Finance, or a related field. Experience in data support, IT helpdesk, or technical support, ideally within finance. Strong command of Python and data libraries. Proficiency with data systems, pipelines, and APIs. Experience with JIRA or similar project management tools. Strong problem-solving skills, communication abilities, and attention to detail. Base salary range for this position is $150,000 to $180,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Location: New York Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. The successful candidate will join QRT’s established Data Centre Operations team. Working closely with Network Engineering and wider infrastructure teams, you will help deploy, maintain and support the physical technology infrastructure used across QRT’s global data centre locations. Your Future Role within QRT Support the physical installation, maintenance and decommissioning of servers, network switches and other data centre equipment. Rack, stack, cable and label equipment to a consistently high standard. Install and manage copper, fibre and power cabling, including patching between devices and patch panels. Carry out hardware break-fix activities, including replacing failed components, cables, optics, power supplies and other parts. Assist with new equipment deployments, upgrades, capacity expansions and site decommissions. Complete basic hardware checks and troubleshooting on servers, switches, power equipment and connectivity. Work from build documents, rack elevations, patching schedules and technical instructions. Support hardware deliveries, stock management, spare parts, equipment movements and site logistics. Work with colocation providers, vendors, remote hands and onsite engineers to complete planned and reactive work. Help maintain high standards of data centre cleanliness, cabling, labelling, security and general operational discipline. Support planned work and break-fix activities across QRT’s global data centre environment. Take part in out-of-hours and weekend work where required, including planned changes, deployments and urgent break-fix activities. Participate in an out-of-hours on-call rota once suitable training and experience have been completed. Your Present Skillset: Some experience working in a data centre, IT infrastructure, network operations, hardware support or similar technical environment. Hands-on experience installing or supporting servers, network devices, cabling or other IT hardware. Basic understanding of servers, network switches, fibre, copper cabling and power connections. A practical and methodical approach to physical work, troubleshooting and problem solving. Strong attention to detail, particularly around cabling, labelling, documentation and build quality. Comfortable following technical instructions, procedures and change plans. Able to work safely and carefully within live data centre environments. Good communication skills and willingness to work with internal teams, vendors and third-party engineers. Organised and comfortable managing tasks, equipment, stock and documentation. Willingness to learn new technologies and develop broader knowledge of data centre infrastructure. Comfortable working as part of a globally distributed team. Willingness to travel internationally when required. Flexibility to carry out evening, overnight and weekend work when needed. Willingness to participate in an out-of-hours on-call rota after completing the required training. Base salary range for this position is $150,000 to $180,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Location: Paris, Zurich Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. We operate one of the most demanding data infrastructures in finance, supporting mission-critical distributed systems across multiple database and streaming platforms, with strict requirements around availability and performance. Our environment spans both on-prem infrastructure and AWS, with a strong focus on standardization, automation, and Kubernetes-based orchestration. We are looking for an experienced Senior Data Platform Engineer to join our DevOps team in Paris. This is a senior, hands-on role for an engineer who can challenge and reshape our existing infrastructure, set technical direction, and raise the bar across the team . This role is fully on-site , with a strong focus on ensuring the reliability and scalability of our production data infrastructure. Your future role within QRT: This role sits at the intersection of data engineering and infrastructure engineering, focused on architecting reliable, scalable, and high-performance data platforms. You will bring an independent and critical perspective, identifying weaknesses in the existing stack, challenging current design decisions, and helping drive the technical roadmap. Your responsibilities will include: Owning the architecture, reliability, and performance of production data systems (ClickHouse, CockroachDB, Trino, etc.) Evaluating the existing infrastructure, identifying architectural gaps, and driving improvements Designing and operating database clusters on Kubernetes (via operators) at scale Setting standards and best practices for data pipelines (ingestion, transformation, replication) Driving and maturing Infrastructure-as-Code practices (Terraform, Helm) Operating and evolving storage and data platforms across on-prem (VAST) and AWS (S3, EMR, MSK, RDS, EKS) Establishing standards for Docker images and CI/CD workflows for data services Defining and maintaining AWS IAM policies, permissions, and security best practices Leading complex troubleshooting across the stack (databases, OS, storage, networking) Defining and improving observability practices (metrics, alerting, capacity planning) Mentoring engineers and collaborating with engineering, data, and research teams to influence technical decisions Your present skillset: 8+ years in DevOps, Data Platform Engineering, or similar, with experience owning production infrastructure at scale Deep production experience with distributed data systems (e.g. ClickHouse, Trino, EMR), including performance tuning and architectural decision-making Expert-level Kubernetes experience (stateful workloads, Helm, operators), ideally at significant scale Extensive Infrastructure-as-Code experience (Terraform, Helm, etc.), including defining standards and reusable patterns Strong knowledge of the AWS data ecosystem (S3, EKS, EMR, MSK, RDS) Deep understanding of AWS IAM and security best practices Hands-on experience with Docker and CI/CD pipelines Solid experience designing and operating data pipelines (Kafka, Spark, Airflow, etc.) Strong Linux fundamentals and scripting (Python and/or Bash) Deep understanding of database reliability (replication, backups, failover) Demonstrated ability to independently assess complex systems, challenge existing designs, and drive technical improvements Strong communication skills, with the ability to influence stakeholders and mentor other engineers Nice to have: OLAP / high-throughput systems experience at scale Experience with VAST Data or similar storage systems Familiarity with Iceberg, Delta Lake or Hudi Observability tools (Prometheus, Grafana, OpenTelemetry) GitOps tools (ArgoCD, Flux) CKA/CKAD or equivalent deep Kubernetes expertise Programming in Go, Rust, or Python Knowledge of Parquet/Arrow and query engines AWS certifications Prior experience in a technical lead or staff-level role QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm. Your future role within QRT This team is integral to the firm’s success. As such, your responsibilities will include: Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats Working with Engineers to automate and optimise your code, ensuring robust data extraction processes Managing the end-to-end process of onboarding new datasets Proactively solving data related problems to minimise time to production Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit Your present skillset 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering. Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy Demonstratable interest in financial markets and the application of data in its analysis and understanding Experience working with both traditional and alternative financial datasets Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors Ability to work in a high-performance, high-velocity environment QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role at QRT: We are looking for an exceptional Software Engineer to be an integral member of the Data and Lifecycle team. We work closely with trading and research functions to provide trade and position lifecycle automations (corporate actions, expiries, coupon payments, etc), maintain reference data, handle internal and external reporting and generate reports for Front office use across different teams. This position has a specialized focus as an SME for Derivatives - Reference Data and Lifecycle . This high-visibility position will directly impact trading and business operations by providing expert guidance on equity-related reference data, events and automating complex lifecycle processes. Your responsibilities will include: Be involved in the design and implementation of scalable, high-performance solutions for trade and position lifecycle automations for derivative products, ensuring accuracy and operational efficiency. Ensure the availability and quality of reference data for different types of derivatives traded by QRT. Partner closely with a variety of stakeholders and maintain alignment with business needs. Your present skillset: 4+ years of work experience in a quantitative trading environment Deep understanding of derivatives (especially futures and options) with regards to reference data and the asset’s lifecycle events In depth knowledge of how derivatives are treated in different markets / exchanges. Advanced programming skills, with a drive for delivering strategic solutions. Programming language agnostic. Experience with Python or C# is a plus but should be willing to pick up. Familiarity with SQL and relational databases. Knowledge of testing as part of continuous delivery and integration pipelines. Excellent communication skills, and ability to collaborate effectively in a small, close-knit team. Fluency in English, both written and verbal communication skills QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role at QRT: We are looking for an exceptional Software Engineer to be an integral member of the Data and Lifecycle team. We work closely with trading and research functions to provide trade and position lifecycle automations (corporate actions, expiries, coupon payments, etc), maintain reference data, handle internal and external reporting and generate reports for Front office use across different teams. This position has a specialized focus as an SME for Equities, ETFs Reference Data and Corporate Actions . This high-visibility position will directly impact trading and business operations by providing expert guidance on equity-related reference data, events and automating complex lifecycle processes. Your responsibilities will include: Be involved in the design and implementation of scalable, high-performance solutions for trade and position lifecycle automations for corporate actions, ensuring accuracy and operational efficiency. Ensure the availability and quality of reference data for diverse asset types, with a particular emphasis on equities and corporate actions. Partner closely with a variety of stakeholders and maintain alignment with business needs. Validate systems and procedures related to reference data and corporate actions, ensuring robust trade/position checks and alignment with brokers and fund administrators. Your present skillset: Deep understanding of equities, ETFs and their derivatives with regards to reference data and corporate actions Advanced Python programming, design, and architecture. Familiarity with SQL and relational databases. Experience with C# is a plus Knowledge of testing as part of continuous delivery and integration pipelines. Excellent communication skills, and ability to collaborate effectively in a small, close-knit team. Fluency in English, both written and verbal communication skills QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role at QRT: We are looking for an exceptional Software Engineer to be an integral member of the Data and Lifecycle team. We work closely with trading and research functions to provide trade and position lifecycle automations (corporate actions, expiries, coupon payments, etc), maintain reference data, handle internal and external reporting and generate reports for Front office use across different teams. This position has a specialized focus as an SME for Derivatives - Reference Data and Lifecycle . This high-visibility position will directly impact trading and business operations by providing expert guidance on equity-related reference data, events and automating complex lifecycle processes. Your responsibilities will include: Be involved in the design and implementation of scalable, high-performance solutions for trade and position lifecycle automations for derivative products, ensuring accuracy and operational efficiency. Ensure the availability and quality of reference data for different types of derivatives traded by QRT. Partner closely with a variety of stakeholders and maintain alignment with business needs. Your present skillset: 4+ years of work experience in a quantitative trading environment Deep understanding of derivatives (especially futures and options) with regards to reference data and the asset’s lifecycle events In depth knowledge of how derivatives are treated in different markets / exchanges. Advanced programming skills, with a drive for delivering strategic solutions. Programming language agnostic. Experience with Python or C# is a plus but should be willing to pick up. Familiarity with SQL and relational databases. Knowledge of testing as part of continuous delivery and integration pipelines. Excellent communication skills, and ability to collaborate effectively in a small, close-knit team. Fluency in English, both written and verbal communication skills QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role at QRT: We are looking for an exceptional Software Engineer to be an integral member of the Data and Lifecycle team. We work closely with trading and research functions to provide trade and position lifecycle automations (corporate actions, expiries, coupon payments, etc), maintain reference data, handle internal and external reporting and generate reports for Front office use across different teams. This position has a specialized focus as an SME for Equities, ETFs Reference Data and Corporate Actions . This high-visibility position will directly impact trading and business operations by providing expert guidance on equity-related reference data, events and automating complex lifecycle processes. Your responsibilities will include: Be involved in the design and implementation of scalable, high-performance solutions for trade and position lifecycle automations for corporate actions, ensuring accuracy and operational efficiency. Ensure the availability and quality of reference data for diverse asset types, with a particular emphasis on equities and corporate actions. Partner closely with a variety of stakeholders and maintain alignment with business needs. Validate systems and procedures related to reference data and corporate actions, ensuring robust trade/position checks and alignment with brokers and fund administrators. Your present skillset: Deep understanding of equities, ETFs and their derivatives with regards to reference data and corporate actions Advanced Python programming, design, and architecture. Familiarity with SQL and relational databases. Experience with C# is a plus Knowledge of testing as part of continuous delivery and integration pipelines. Excellent communication skills, and ability to collaborate effectively in a small, close-knit team. Fluency in English, both written and verbal communication skills QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. You will join QRT’s Data team as a Software Engineer, working at the intersection of engineering, trading, and research. Your focus will be on delivering scalable systems for reference data management, regulatory and external reporting, and front-office analytics. This role offers direct visibility across the business and the opportunity to collaborate with stakeholders across Execution, Engineering, and Research teams. Every project you work on will contribute to operational efficiency and trading decision-making. Your role at QRT This is primarily a hands-on engineering role (≈80% development), with a smaller component (≈20% support and system ownership) focused on maintaining robustness, reliability, and data quality in production. You’ll work closely with trading, research, risk, and operations teams, gaining strong exposure to the business while building scalable, high-performance systems. What you’ll work on Designing and building scalable, high-performance systems for trade and position lifecycle management Developing solutions to automate lifecycle events such as corporate actions, expiries, and cash flows across asset classes Building and maintaining high-quality reference data platforms used across trading and research Delivering real-time and end-of-day reporting pipelines for internal and external stakeholders Ensuring data accuracy, integrity, and consistency across systems and workflows Contributing to system validation, controls, and operational robustness, including alignment with brokers and fund administrators Collaborating closely with stakeholders to translate business needs into reliable technical solutions Writing well-tested, maintainable code and contributing to CI/CD and deployment pipelines Supporting production systems and continuously improving reliability, monitoring, and performance What we’re looking for 5–10 years of software engineering experience, ideally in a high-performance or data-intensive environment Strong programming skills in Python (experience with C# is a plus) Solid understanding of software design, architecture, and scalable systems Experience working with SQL and relational databases Familiarity with testing frameworks and CI/CD practices Domain experience (one or more is valuable, not required). We’re interested in engineers with exposure to financial markets, particularly: Trade and position lifecycle systems Equities, ETFs, futures, or options Corporate actions and reference data Market structure and exchange-specific behaviour Deep expertise in a single asset class is not required—but an interest in learning and working in a trading environment is important. What will set you apart Experience building systems in a quantitative trading or financial environment Strong problem-solving skills with a focus on performance, scalability, and data quality Ability to operate in a high-impact, fast-paced environment with evolving requirements Clear communication skills and a collaborative mindset Why join QRT? Work on business-critical systems with direct impact on trading outcomes Join a core engineering team with significant ownership and autonomy Collaborate with traders, researchers, and engineers in a highly technical environment Tackle complex data and systems challenges at scale QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Paris Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. This team is integral to the firm’s success. We are seeking a technically skilled Data Support Engineer to support quantitative researchers and traders in navigating and using extensive datasets. You will support all data users, contribute to documentation, and ensure data quality. Your future role within QRT Provide first-line support to researchers and traders for data access ad usage. Collaborate with data engineers to resolve data issues. Onboard new hires and train them on using data tools and processes efficiently. Manage JIRA workflows, track support requests, and ensure timely resolution of data issues. Contribute to data documentation. Contribute to extending data coverage (live collection and backfills) Your present skillset A bachelor’s degree in Data Science, Computer Science, Finance, or a related field. Experience in data support, IT helpdesk, or technical support, ideally within finance. Strong command of Python and data libraries. Proficiency with data systems, pipelines, and APIs. Experience with JIRA or similar project management tools. Strong problem-solving skills, communication abilities, and attention to detail. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.