Responsibilities:

  • Own and prioritize concurrent production data-science projects and systems, turn 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 across UTXO, EVM, and other blockchain data to attribute on-chain activity and uncover customer-relevant insights.
  • Evaluate and pilot techniques such as graph computation, statistical modeling, and machine learning on large-scale on-chain datasets.
  • Improve code, methodology, and workflows; make architectural decisions; define quality metrics; manage dependencies; and balance system health and technical debt with delivery.
  • Align cross-functional stakeholders, explain and defend methodology and results, mentor team members, support onboarding and technical hiring, and share knowledge through documentation and presentations.
  • Collaborate with Research, Global Intelligence, Product, and Engineering to move research into dependable production systems and build tools or platforms that increase team output.

Requirements:

  • Deep expertise in statistics, machine learning, computer science, physics, mathematics, or another quantitative discipline.
  • Expert-level Python and SQL proficiency, 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; blockchain experience is welcome but not required.
  • Experience owning and prioritizing concurrent projects or systems, making architectural and methodological decisions, and driving cross-functional delivery.
  • Strong communication skills, including explaining complex methods, mentoring technical practitioners, and sharing knowledge.

Nice to have: PhD or equivalent quantitative research training; familiarity with Databricks, dbt, Spark/PySpark, or similar large-scale data platforms; experience with Terraform, production data pipelines, shared tools, UTXO, EVM, graph computation, or the cryptocurrency ecosystem.

Employment: Full-time. Remote (London office).