Senior Manager, Data Science

TRM Labs

3d•$210,000 - $230,000•Remote

About The Position

TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure. At TRM Labs, we’re on a mission to build the best blockchain intelligence on earth — and we’re looking for a seasoned Data Science Manager to lead the charge on one of our most foundational initiatives: connecting blockchain activity to real-world entities with unmatched precision and scale. This team tackles one of the most challenging and high-impact problems in blockchain analytics — combining intelligence, data science, and applied machine learning. The role is a unique blend of technical leadership, product strategy, and people management — perfect for someone who thrives in ambiguity and wants to shape how the world understands what’s happening on-chain.

Requirements

Technical depth: You’ve led data science teams in complex, ambiguous environments, and can operate across the stack — from debugging DAGs to modeling strategy.
Product sense: You understand customer problems deeply and can shape product direction through data and experimentation.
Hands-on leadership: You’re not just a people manager. You stay close to the work, unblock your team, and lead by example.
Curiosity & growth mindset: You’re energized by novel problems, seek truth through data, and thrive in fast-paced, scrappy environments.
Strong communicator: You make your thinking legible — to engineers, PMs, and executives — and influence through clarity, not volume.
4+ years of experience managing data science or ML teams.
Proven experience with large-scale data systems (e.g., BigQuery, Snowflake).
Strong programming skills in Python and familiarity with production code practices (git, testing, notebooks).
Bachelor’s degree or higher in a quantitative field (CS, Stats, Physics, Engineering). Advanced degree preferred.
US time zones preferred; at least 6 hours overlap with US Eastern time required.
On-call responsibilities rotate every ~2 months.
AI fluency is a baseline expectation at TRM.
You will be evaluated on applied AI fluency during the interview process.
Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday.
Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger.

Nice To Haves

Advanced degree preferred.

Responsibilities

Lead and mentor a high-performing data science team operating at the intersection of blockchain, intelligence, and machine learning — balancing individual execution with strategic vision.
Drive technical innovation across a diverse stack (e.g., Airflow, BigQuery, Kafka, Python), ensuring our data models and pipelines scale with quality and precision.
Collaborate cross-functionally with engineering, product, and intelligence teams to transform raw blockchain data into insights that power TRM’s products and customer experiences.
Help make TRM the market leader in blockchain Attribution, setting new standards for accuracy, trust, and usability in blockchain data.
Recruit, develop, and retain top talent — and play a critical role in growing the team’s technical and product maturity.
Understands the importance of customer-facing incidents (if and when they occur). Is willing to push the boundaries of a simple work day if an incident arises to ensure the issue is mitigated.
Incident prevention is squarely in the control and ownership of engineering & DS leadership and correctly prioritizes the type of work to prevent customer incidents.
Effectively uses AI and self-driven investigation to understand the capabilities and boundaries of partner team infrastructure.