Data Scientist

We are seeking an Ontologically Aware Data Scientist to design, build, and operationalize knowledge‑centric AI/ML systems that integrate ontology engineering, semantic data modeling, and advanced analytics. This role blends deep experience with RDF/OWL/SHACL and graph data models with practical machine learning, natural‑language processing, and context engineering. You will develop semantic foundations and AI-driven tooling that enable multiple organizations to communicate using shared ontologies and that support natural‑language‑to‑SPARQL interfaces with reduced hallucination.

Responsibilities

• Develop and maintain logical, semantically rich, extensible ontologies (RDF/OWL/SKOS) aligned to foundational/top‑level ontologies (BFO, DOLCE, CCO, OBO Foundry).
• Build and evolve canonical vocabularies that unify heterogeneous datasets across organizational boundaries.
• Design, implement, and maintain knowledge graphs and semantic data models using AnzoGraph including modeling tradeoffs, query optimization, and production operations.
• Create SHACL validation layers; run regular quality checks to ensure consistency, backward compatibility, and schema integrity.
• Write performant SPARQL queries; develop mapping views, CONSTRUCT transformations, and federated semantic integrations.
• Develop hybrid ontology–GenAI capabilities, including natural‑language‑to‑SPARQL pipelines with context engineering frameworks (e.g., DSPy) to reduce hallucination and improve schema grounding.
• Apply machine learning techniques—classification, embedding‑based retrieval, entity resolution, and model fine‑tuning—to support ontology evolution, reification, and inference.
  
  
• Partner with cross‑functional teams (Data Engineering, Developers, content owners) to understand information needs and deliver semantic/analytical solutions.
• Produce clear, accessible technical documentation; deliver onboarding and training for both technical and non‑technical users.
• Apply strong software engineering discipline to semantic assets: version control, code review, automated SHACL/dbt tests, CI/CD pipeline alignment.
• Support both new development and ongoing operations/maintenance across unclassified and classified environments.

Required Qualifications

• A bachelor’s degree and 8 years of relevant experience OR a Master’s degree with 6 years of relevant experience OR A PhD with 3 years of relevant experience
• Prefer an advanced degree in Philosophy, Computer Science, Information Science, or a quantitative field, or equivalent experience.
• Deep proficiency in ontology languages (RDF, OWL, SHACL) and vocabularies (SKOS).
• Strong SPARQL skills; experience with semantic ETL, query optimization, and graph reasoning.
• Proficiency in Python (plus R/Java as needed) for data science, graph processing, and ML model development.
• Strong engineering practices: Git, PR workflow, testing/validation, CI/CD.
• Active TS adjudication with ability to obtain the SCI/CI Poly.

Desired Qualifications

• Hands-on experience with ontology/graph platforms such as Protégé, AnzoGraph, Stardog, PoolParty, or Semaphore.
• Experience integrating disparate datasets into a unified semantic model and writing effective production-grade queries.
• Familiarity with upper ontologies (BFO, DOLCE, Common Core Ontologies, OBO Foundry).
• Knowledge of machine learning, including supervised/unsupervised methods, embeddings, and model fine‑tuning.