Senior Data Scientist Knowledge Layer
Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.
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
You will design, build, and deploy machine learning models for knowledge extraction, entity resolution, graph learning, and relationship discovery. You will evaluate models, integrate them into production APIs, perform exploratory data analysis, evolve knowledge graphs and ontologies, and own ML components from experimentation through iteration.
Requirements
- 5+ years of data science, machine learning engineering, or applied ML experience
- Python
- Production machine learning
- NLP or information extraction
- Named Entity Recognition
- Text classification
- Embedding-based approaches
- Knowledge graphs
- Graph data
- Graph-based machine learning
- API and service development
- Software engineering
- Communication
Responsibilities
- Design, build, and productionize machine learning models
- Build models for knowledge extraction, entity linking, graph learning, and entity resolution
- Evaluate machine learning models and frameworks
- Integrate ML models into production services and APIs
- Contribute to knowledge graph and ontology design
- Perform exploratory data analysis
- Own ML experimentation, evaluation, deployment, and iteration
- Shape applied ML best practices
Benefits
- Eligibility to participate in TRM's equity plan
- Approved travel, lodging, and workspace for required work weeks
Hiring Process
Recruiter intro → hiring manager interview → first-round interviews → final panel case study → references → offer.