Senior Data Scientist, Attribution

Role Description

As a Senior Data Scientist, Attribution, you will be embedded within a specific risk category (e.g., Sanctions, Cybercrime, Counter Terrorism) and own the attribution algorithms that drive direct customer outcomes — from seizing illicit funds to disrupting crypto-enabled crime networks. You'll operate as equal parts Subject Matter Expert and Data Scientist, translating deep domain knowledge into production-grade intelligence.

The impact you'll have here:

• Own end-to-end attribution for a risk category: identify high-impact targets, build algorithms (heuristics, ML models, AI agents), and ship to production.
• Collaborate tightly with — and become — a Subject Matter Expert for your category, translating customer and GTM needs into actionable intelligence.
• Navigate all intelligence layers (Network / On-chain / Protocol) to uncover patterns competitors can't replicate.
• Ship production-quality code — heuristics, ML models, and data pipelines — with rigorous evaluation and scalable architecture.
• Drive measurable outcomes: billions in illicit funds traced, seized, or prevented.

Qualifications

• Quantitative background (Computer Science, Statistics, Engineering, Economics, Physics).
• Strong problem-solving mindset: gets to the root cause, leverages creativity, and thrives in ambiguity with a hypothesis-driven, iterative approach.
• Demonstrated domain curiosity — ability to absorb and apply expertise in blockchain, fraud, money laundering, or cybercrime.
• 6+ years in an analytical role with strong SQL, Python, and AI-assisted coding tools (Cursor, Claude Code).
• Experience with distributed data systems (Spark, BigQuery, Airflow) and shipping production code.
• Strong async communication (Loom, Slack, Notion) and ability to own work independently in a remote environment.
• Bonus: Deep ML experience, prior work in crypto, financial crime, or financial institutions.

Requirements

• On-call responsibilities: Analytics on-call (< 1 hr/day monthly) and Data Science on-call (1-2 hrs/day every 3 months).

Benefits

• Fully remote and globally distributed work environment.
• Most overlap occurs 7am–12pm PST for meetings and collaboration.
• All team members must have at least 4-hour overlap with PST business hours.