Data Scientist

About Peraton

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we're keeping people around the world safe and secure.

About The Role

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.

Qualifications

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.

Details

Target Salary Range: $135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.

Benefits Statement: Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.

Application Duration Statement: The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.

EEO:Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.