Senior Data Scientist, Graph ML
6.0/10
TRM
Not specified
Remote
senior
6 days ago
aidatatechPythonMachine LearningNLPKnowledge Graphs
AI Summary
The vacancy is strong in task clarity and requirements but lacks compensation details.
Check Match — Just drop your CV
See your fit for Senior Data Scientist, Graph ML in seconds.
Description
The impact you will have
- •Design, build, and productionize machine learning models focused on:
- •Knowledge extraction from unstructured data (e.g., NER, entity linking)
- •Graph-based learning and inference
- •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
Life at TRM
- •Priorities and targets to change quickly as we experiment and iterate
- •Work that often requires operating with a high degree of ambiguity
- •A high level of personal ownership and accountability
- •Close collaboration across teams and functions
- •Frequent, high-touch communication
- •Creative problem solving and out-of-the-box thinking
- •A pace that rewards urgency, adaptability, and outcomes
Requirements
What we’re looking for
- •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
Loading similar jobs...