Senior Data Scientist, Graph ML

TRM Labs

5d • Remote

About The Position

TRM Labs is seeking a Full Stack Data Scientist to join their Knowledge Layer team. This team focuses on extracting, structuring, and analyzing knowledge from large-scale, unstructured data, operating at the intersection of knowledge graphs, entity resolution, graph extraction, and graph analytics. The role requires a machine learning and data science expert, particularly in knowledge extraction and graph-based ML, to enhance and scale the team's capabilities. This position offers the opportunity to work end-to-end, from model selection and experimentation to productionizing ML systems and APIs.

Requirements

• 5+ years of experience in data science, machine learning engineering, or applied ML.
• Strong programming experience in Python.
• Hands-on experience building, training, or deploying machine learning models in production.
• Familiarity with NLP or information extraction techniques, such as Named Entity Recognition (NER), text classification, or embedding-based approaches.
• Experience or strong interest in knowledge graphs, graph data, or graph-based ML.
• Solid software engineering fundamentals, including building and maintaining APIs or services.
• Ability to translate ambiguous problem spaces into practical ML solutions.
• Strong communication skills and comfort collaborating with engineers across disciplines.

Responsibilities

• Design, build, and productionize machine learning models focused on knowledge extraction from unstructured data (e.g., NER, entity linking), graph-based learning and inference, and entity resolution and relationship discovery.
• Evaluate and leverage existing ML models and frameworks to solve real-world problems efficiently.
• Partner closely with backend and graph engineers to integrate ML models into production services and APIs.
• Contribute to the design and evolution of knowledge graphs and ontologies.
• Perform exploratory data analysis (EDA) to inform modeling decisions and system design.
• Own ML components end-to-end, including experimentation, evaluation, deployment, and iteration.
• Help shape best practices for applied ML within the Knowledge Layer team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed