Data Scientist — Blockchain Intelligence

Stack

Responsibilities

• ▹Design, test, and ship clustering and attribution heuristics, measured with real precision/coverage metrics rather than vibes
• ▹Own data end to end: pull, clean, join, and model large on-chain datasets
• ▹Build and maintain pipelines that take a heuristic from notebook to production, including backfills, incremental runs, and validation
• ▹Investigate edge cases such as mixers, bridges, exchange hot wallets and consolidation patterns, translating findings into repeatable logic
• ▹Partner with investigations and product teams to define what correct looks like, benchmarking against ground truth
• ▹Prototype quickly, then harden what works

Requirements

• ▹4+ years building data science or data engineering systems that actually shipped, not just notebooks
• ▹Strong Python and SQL, comfortable with large datasets and the gotchas of joins, dedup, and skew at scale
• ▹Solid grasp of clustering, graph/network analysis, or entity resolution, with a habit of validating results
• ▹Ability to reason about precision vs. coverage trade-offs and defend metrics
• ▹Self-directed: able to scope an ambiguous problem, get the data, and drive it to a result

Soft skills

About the company

Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, and law enforcement and government agencies; headquartered in New York with offices in Singapore, Bangalore and London, having raised over $27M.