Senior Data Scientist, Blockchain Insights
TRM LabsUnited States$170k – $195kPosted 21 February 2026
Job Description
Build a Safer World.
TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all.
As a Senior Data Scientist on the Insights team, you will play a central role in transforming TRM’s intelligence into compelling, defensible narratives. Working closely with engineers, data scientists and editors, you’ll uncover patterns and connections across both on-chain and off-chain data, producing insights that inform TRM’s flagship reports and investigations.
Your work won’t stop at research. You will actively discover new intelligence, validate and extend TRM’s attribution, and communicate findings back into our attribution pipelines and products. The insights you generate will strengthen TRM’s ability to surface emerging threats — from scams and fraud to complex laundering schemes — ensuring that our intelligence products remain the most reliable and impactful in the industry.
The impact you will have:
Push the frontier of blockchain attribution : Design and apply innovative techniques to surface hidden relationships across entities, transactions, and categories of interest.
Advance the science of blockchain intelligence : Uncover patterns in vast and complex networks that help redefine what’s possible in this space.
Deliver impactful insights at scale : Build pipelines, models, and frameworks that generate timely, high-quality intelligence for both internal teams and external stakeholders.
Reduce time-to-insight dramatically : Help TRM and its partners respond to emerging risks faster than ever before.
Collaborate across disciplines : Work closely with subject matter experts and engineers to validate heuristics, enhance attribution models, and operationalize new approaches into production systems.
Empower global institutions : Provide insights that support governments, law enforcement, and financial organizations in combating fraud, financial crime, and national security threats., including for former FBI, Secret Service, and Europol agents.
Shape the future of data science at TRM : Identify new opportunities, propose bold ideas, and set standards for how intelligence is generated and consumed.
Mentor and inspire peers : Contribute to a culture of intellectual curiosity, rigor, and continuous improvement.
What we're looking for:
Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering, Economics or Physics. Advanced degree preferred.
You have 6+ years of experience working in an analytical role.
You have proven experience with at least one programming language (Python preferred) and are comfortable developing code in a team environment (e.g. git, notebooks, testing).
You have a working knowledge of relational databases, (e.g. SQL)
You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data and identify targets for performance
You have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
The following represents the expected range of compensation for this role:
The estimated base salary range for this role is $170,000 - $195,000. Please note that the base range is applicable to the US and will be different depending on the country.
Additionally, this role may be eligible to participate in TRM’s equity plan.
Life at TRM
We are building a safer world. That promise shows up in how we work every day.
TRM runs fast. Really fast. We’re a high‑velocity, high‑owners ... (truncated, view full listing at source)
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