Staff Data Scientist

Requirements:

• 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.

Nice to have:

• 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.

What you'll be doing:

• 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.

Perks and benefits:

AI fluency is tied directly to how we measure performance and how we plan to win. There is no substitute for your own curiosity. We provide the tools, workflows, and space to experiment - but the expectation is that you develop these capabilities yourself, bring ideas, and collaborate across teams to reinvent the way work gets done. We are not using AI to do less. We are using it to do what was never possible before.

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 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.