Senior Data Scientist (Graph ML)

Senior Data Scientist, Graph ML

Company

TRM Labs

Conditions

21 hours agoSenior North America Remote Full Time Data Science Jobs by TRM Labs

Skills

Graph Algorithm Knowledge Graph Nlp Machine Learning Software Engineering Model Deployment Python Exploratory Data Analysis Api Knowledge Extraction Named Entity Recognition Entity Linking Graph Machine Learning Entity Resolution

About the Role

You will design, build, and productionize machine learning models focused on knowledge extraction (e.g., NER and entity linking), graph-based learning, and entity resolution. You will evaluate and leverage existing ML models and frameworks, perform exploratory data analysis to inform modeling decisions, and own ML components end-to-end including experimentation, evaluation, deployment, and iteration. You will partner closely with backend and graph engineers to integrate models into production services and APIs, contribute to the design and evolution of knowledge graphs and ontologies, and help establish best practices for applied ML.

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 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

Responsibilities

• Design build and productionize ML models for knowledge extraction
• Develop graph-based learning and inference models
• Perform entity resolution and relationship discovery
• Evaluate and leverage existing ML models and frameworks
• Integrate ML models into production services and APIs
• Contribute to design and evolution of knowledge graphs and ontologies
• Perform exploratory data analysis to inform modeling and system design
• Own end-to-end ML components including experimentation evaluation deployment and iteration
• Establish best practices for applied machine learning

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