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Design, develop, and maintain formal domain ontologies, taxonomies, and semantic schemas to support enterprise AI and analytics. Collaborate with engineering teams to ground LLM workflows and GraphRAG pipelines in trusted enterprise context.
This is a remote position.
We are looking for a Senior Data Scientist (Ontology & Semantic Modeling) with a strong background in formal ontologies and semantic modeling to design the foundational knowledge layer for our enterprise AI and analytics initiatives. You will bridge complex business domains and technical data architectures, ensuring our data models and AI agents operate on unambiguous, machine-readable domain semantics.
Key Responsibilities:
Design, develop, and maintain formal domain ontologies, taxonomies, and semantic schemas (OWL, RDF, RDFS, SHACL).
Translate complex business rules, domain concepts, and entity relationships into structured semantic models.
Collaborate closely with Knowledge Graph Engineers and Agentic AI Engineers to ground LLM workflows and GraphRAG pipelines in trusted enterprise context.
Establish ontology governance, versioning standards, and validation rules across cross-functional data sources.
Align enterprise semantic layers with analytical platforms (Databricks) and operational CRM ecosystems.
5+ years of experience in Ontology Engineering, Semantic Web technologies, or Knowledge Graph-focused Data Science.
Hands-on expertise with semantic standards and query languages (OWL, RDF, SPARQL, SHACL, SKOS).
Proven experience building enterprise ontologies or semantic layers for complex domains (e.g., Life Sciences, Healthcare, Finance, or Supply Chain).
Strong programming skills in Python and familiarity with graph databases (e.g., RDF triplestores or property graphs) and knowledge graph workflows.
Excellent communication skills to elicit domain knowledge from business stakeholders and translate it into formal specifications.
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