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Chainalysis is seeking a Staff Data Scientist to join the Research and Intelligence organization in London. You will lead analytical, statistical, and machine-learning work across UTXO and EVM blockchains, developing behavioral heuristics, graph algorithms, statistical models, and machine-learning techniques that power advanced blockchain analysis. Much of this work is state-of-the-art and ahead of academia.
In this role, you will own and prioritize multiple concurrent production data-science projects or systems, translating broad problem statements into actionable work while managing evolving requirements and delivering measurable outcomes. You will design, develop, and validate novel analytical methods, statistical models, behavioral heuristics, and algorithms across blockchain data to attribute on-chain activity and uncover customer-relevant insights. You will stay current on advances in data science and blockchain analysis, evaluating and piloting techniques such as graph computation, statistical modeling, and machine learning on large-scale on-chain datasets.
You will 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. You will drive cross-functional alignment by clearly articulating and defending methodology and results, challenging assumptions when warranted, and building consensus as requirements evolve. You will mentor team members across levels within your domain, support onboarding, contribute to technical hiring, and share knowledge through documentation and presentations. You will 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.
The company emphasizes that AI is not a feature but a new way of working at Chainalysis. AI fluency is tied directly to performance measurement and winning strategy. You are expected to take ownership of AI output quality, develop AI capabilities yourself, bring ideas, and collaborate across teams to reinvent how work gets done.
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
- Demonstrated ability to own and prioritize multiple concurrent projects or systems, make sound architectural and methodological decisions, and drive cross-functional stakeholders toward delivery
- 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:
- 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
TECHNOLOGIES: Python, SQL, Databricks, Dbt, PySpark/Spark, Terraform, AWS, Postgres
