Chainalysis

Senior Data Scientist

6.0/10

Chainalysis

Not specified
Office / on-site
senior
about 11 hours ago
aicryptodataweb3PythonSQLDatabricksDBTPySparkSparkTerraformAWS

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The vacancy is strong in task clarity and requirements but lacks compensation details.

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Description

What you'll do

In this role, you'll:

  • โ€ขOwn the execution of one or more production data science projects, translating broad problem statements into well-scoped tasks and credible analytical results that meet stakeholder expectations.
  • โ€ขDesign, develop, and validate novel behavioral heuristics and algorithms over EVM (and other) blockchain data to attribute on-chain activity and uncover new insights.
  • โ€ขApply advanced techniques including graph computation, statistical modeling, and machine learning to large-scale on-chain datasets.
  • โ€ขIdentify and resolve inefficiencies in code, methodology, and workflows; ensure your work integrates cleanly into our production data and tooling stack.
  • โ€ขClearly articulate and defend methodology and results to both technical and non-technical stakeholders, maintaining alignment through consistent communication.
  • โ€ขMentor junior team members, contribute to technical hiring, and share knowledge.
  • โ€ขCollaborate closely with peers to bring research from prototype to production.

Requirements

We're looking for candidates who have:

  • โ€ขA PhD in computer science, machine learning, statistics, physics, mathematics, or a related technical field โ€“ or equivalent industry experience working on advanced, data-intensive problems.
  • โ€ขExpert-level proficiency in Python and SQL, with a track record of writing clean, testable, production-quality code.
  • โ€ขDemonstrated experience applying advanced analytical techniques (e.g. graph algorithms, ML, statistical inference) to large, messy datasets.
  • โ€ขComfort working with EVM-based blockchain data, or strong evidence of the aptitude to ramp up quickly on EVM data structures and protocols.
  • โ€ขA demonstrated ability to take ownership of projects: decomposing requirements, driving them to completion, and proactively seeking clarity from stakeholders.
  • โ€ขAn analytical, open-minded approach to problem solving โ€“ comfortable navigating ambiguity and willing to dive into problems outside your day-to-day scope.
  • โ€ขStrong written and verbal communication skills, including the ability to explain complex methodology to diverse audiences.
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