About Chainalysis
Chainalysis provides a blockchain data platform that connects digital asset movements to real-world services. Organizations use its blockchain data and AI to investigate illicit activity, manage risk exposure, and develop market solutions. Its mission is to build trust in blockchains while supporting safety, security, growth, and innovation.
Responsibilities
•Own and prioritize concurrent production data science projects or systems, translate broad problem statements into actionable work, manage evolving requirements, and deliver measurable outcomes
•Design, develop, and validate analytical methods, statistical models, behavioral heuristics, and algorithms using blockchain data to attribute on-chain activity and uncover customer-relevant insights
•Evaluate and pilot data science and blockchain analysis techniques, including graph computation, statistical modeling, 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; manage dependencies; and balance system health and technical debt against delivery
•Drive cross-functional alignment by explaining and defending methodologies and results, challenging assumptions, and building consensus as requirements evolve
•Mentor team members, support onboarding and technical hiring, and share knowledge through documentation and presentations
•Collaborate across Research, Global Intelligence, Product, and Engineering to move research into production systems and build tools or platforms that increase team output
•Take ownership of AI-generated output and ensure its quality; experiment with AI tools and workflows, develop AI capabilities, share ideas, and collaborate across teams to improve how work is 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 experience writing clean, testable, production-quality code
•Experience applying advanced analytical techniques, such as graph algorithms, machine learning, or statistical inference, to large, messy datasets
•Ability to learn unfamiliar technical domains and data models quickly
•Ability to own and prioritize concurrent projects or systems, make sound architectural and methodological decisions, and drive cross-functional stakeholders toward delivery
•Analytical, open-minded approach to problem-solving, comfort with ambiguity, and willingness to work beyond day-to-day scope
•Strong written and verbal communication skills, including explaining complex methodologies to diverse audiences, mentoring technical practitioners, and sharing knowledge
Nice to have
•A PhD or equivalent research training in a quantitative field
•Familiarity with Databricks, dbt, Spark/PySpark or similar large-scale data platforms
•Experience modifying infrastructure-as-code such as Terraform
•Contributing to production data pipelines, building shared tools or platforms and onboarding others
•Experience with UTXO, EVM or other blockchain data, graph computation, or the cryptocurrency ecosystem
Conditions
Not specified in the posting.
