Senior Data Scientist Graph ML
Skills
About the Role
You will design and build machine learning models that extract knowledge from unstructured data and perform graph based learning and inference. You will own ML components end to end from experimentation to deployment and collaborate with backend and data engineering teams to productionize solutions. You will contribute to knowledge graphs and ontologies and help shape practical ML practices within the Knowledge Layer team.
Requirements
- 5+ years of experience in data science machine learning engineering or applied ML
- Strong programming experience in Python
- Hands on experience building training 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
- Perform graph based learning and inference and advance entity resolution and relationship discovery
- Evaluate and leverage existing ML models and frameworks to solve real world problems efficiently
- Collaborate 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 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