Senior Data Scientist, Attribution — Remote (LATAM)

TRM Labs; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

TRM Labs seeks a Senior Data Scientist, Attribution to own attribution algorithms within a risk category such as Sanctions, Cybercrime, or Counter Terrorism. You will function as both a Subject Matter Expert and a data scientist, translating domain knowledge into production-grade intelligence and customer outcomes.

The role emphasizes end-to-end attribution, collaboration with SMEs and engineers, and shipping robust data pipelines.

Qualifications

• Requires 6+ years in an analytical role with strong SQL, Python, and AI-assisted coding tools.
• Experience with distributed data systems (Spark, BigQuery, Airflow) and shipping production code.
• Strong async communication (Loom, Slack, Notion) and ability to work independently in a remote environment.

Responsibilities

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

Skills

SQL

Python

Analytical thinking

Problem-solving mindset

Domain curiosity

Communication

Education

Bachelor's degree in a quantitative field

Tools

Cursor

Claude Code

Spark

BigQuery

Airflow

Job description

TRM Labs seeks a Senior Data Scientist, Attribution to own attribution algorithms within a risk category such as Sanctions, Cybercrime, or Counter Terrorism. You will function as both a Subject Matter Expert and a data scientist, translating domain knowledge into production-grade intelligence and customer outcomes.

The role emphasizes end-to-end attribution, collaboration with SMEs and engineers, and shipping robust data pipelines.