Senior Manager, Data Science
Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.
Maintainer signals as of 8/23/2026
Funding history
Investors
About TRM Labs
TRM Labs provides blockchain intelligence for investigations and compliance, offering products such as forensics, wallet screening, entity screening, transaction monitoring, and APIs. It serves financial institutions, crypto businesses, and public sector agencies to trace funds, assess risk, and build cases across digital assets.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Lead and mentor a high-performing data science team working across blockchain intelligence and machine learning. Drive scalable, high-quality data models and pipelines, collaborate across engineering, product, and intelligence, and help advance blockchain attribution products while recruiting and developing talent.
Requirements
- 4+ years of experience managing data science or ML teams
- Experience with large-scale data systems such as BigQuery or Snowflake
- Strong Python programming skills and familiarity with git, testing, and notebooks
- Bachelor's degree or higher in a quantitative field; advanced degree preferred
- At least 6 hours of overlap with US Eastern time required
- Experience leading data science teams in complex, ambiguous environments
- Product sense and ability to shape product direction through data and experimentation
- Hands-on leadership, strong communication, and comfort with fast-paced environments
Responsibilities
- Lead and mentor a high-performing data science team
- Drive technical innovation across Airflow, BigQuery, Kafka, and Python
- Collaborate cross-functionally with engineering, product, and intelligence teams
- Advance blockchain attribution products and standards for accuracy, trust, and usability
- Recruit, develop, and retain data science talent