Staff Data Scientist

Chainalysis is inspired by solving the hardest technical challenges and creating products that build trust in cryptocurrencies. We're a global organization who thrive on the challenging work we do and doing it with other exceptionally talented teammates. Our industry changes constantly, and our job is to create user-facing products supported by our best-in-class data, allowing us to adapt to those rapid changes and bring maximal value to our customers.

We're looking for a Staff Data Scientist to join our Research and Intelligence organisation in London. You'll work across flexible, cross-functional squads within the Data Science team, leading analytical, statistical, and machine-learning work across both UTXO and EVM blockchains. The team develops behavioural heuristics, graph algorithms, statistical models, and machine-learning techniques that power some of the most advanced blockchain analysis in the industry. Much of the work is state of the art and ahead of academia; your work will shape the data that fuels Chainalysis products and customers globally.

This role is ideal for someone energised by deeply technical, ambiguous problems at the intersection of statistics, machine learning, algorithms, and large-scale on-chain analysis—and who wants to own multiple projects and systems end to end, shape technical direction, and deliver company-level impact.

• Own and prioritise multiple concurrent production data-science projects or systems, translating broad problem statements into actionable work, managing evolving requirements, and delivering measurable outcomes.

• Design, develop, and validate novel analytical methods, statistical models, behavioural heuristics, and algorithms across UTXO, EVM, and other blockchain data to attribute on-chain activity and uncover customer-relevant insights.

• Stay current on advances in data science and blockchain analysis; evaluate and pilot techniques such as graph computation, statistical modelling, and machine learning on large-scale on-chain datasets.

• Identify and resolve inefficiencies in code, methodology, and workflows; make architectural decisions; define and track quality metrics; understand upstream and downstream dependencies; and balance long-term system health and technical debt against new delivery.

• Drive cross-functional alignment by clearly articulating and defending methodology and results, challenging assumptions when warranted, and building consensus as requirements evolve.

• Mentor team members across levels within your domain, support onboarding, contribute to technical hiring, and share knowledge through documentation and presentations.

• Collaborate across Research, Global Intelligence, Product, and Engineering to move research from prototype to dependable production systems and create tools or platforms that multiply team output.

• Deep expertise in statistics, machine learning, computer science, physics, mathematics, or another quantitative discipline, demonstrated through advanced industry or research work.

• Expert-level proficiency in Python and SQL, with a track record of writing clean, testable, production-quality code.

• Demonstrated experience applying advanced analytical techniques (e.g. graph algorithms, ML, statistical inference) to large, messy datasets.

• Demonstrated ability to learn unfamiliar technical domains and data models quickly; prior blockchain experience is welcome but not required.

• A demonstrated ability to own and prioritise multiple concurrent projects or systems, make sound architectural and methodological decisions, and drive cross-functional stakeholders toward delivery.

• An analytical, open-minded approach to problem solving – comfortable navigating ambiguity and willing to dive into problems outside your day-to-day scope.

• Strong written and verbal communication skills, including the ability to explain complex methodology to diverse audiences, mentor technical practitioners, and share knowledge across a team.

• A PhD or equivalent research training in a quantitative field, and/or familiarity with Databricks, dbt, Spark/PySpark, or similar large-scale data platforms.

• Experience modifying infrastructure-as-code (e.g. Terraform) or contributing to production data pipelines.

• Experience building shared tools or platforms that multiply team output and onboarding others onto them.

• Experience with UTXO, EVM, or other blockchain data, graph computation, and/or the cryptocurrency ecosystem.

• Python

• SQL

• Databricks

• Dbt

• PySpark / Spark

• Terraform

• AWS

• Postgres

Chainalysis is the blockchain data platform, making it easy to connect the movement of digital assets to real-world services. Powered by deep blockchain data and AI, organizations can investigate illicit activity, manage risk exposure, and develop innovative market solutions built on the industry's most trusted blockchain intelligence. Our mission is to build trust in blockchains, blending safety and security with an unwavering commitment to growth and innovation.

At Chainalysis, we believe that diversity of experience and thought makes us stronger. With both customers and employees around the world, we are committed to ensuring our team reflects the unique communities around us. We’re ensuring we keep learning by committing to continually revisit and reevaluate our diversity culture.

We encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, don't hesitate to let us know. You can learn more here. We can’t wait to meet you.