Data Scientist V

VTG • Herndon, VA

3d

About The Position

Byte Systems, a subsidiary of VTG, is seeking a 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.

Requirements

• A bachelor’s degree and 14 years of relevant experience OR a Master’s degree with 12 years of relevant experience OR A PhD with 9 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.

Nice To Haves

• 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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees