Principal Scientist, Data Science (Translational Knowledge Engineering)
Johnson & Johnson
August 13, 2026
Remote friendly (Raritan, NJ)
United States
Clinical Research and Development
Position Summary
- Design and implement semantic and knowledge architecture enabling AI-driven reasoning across the drug discovery and development lifecycle.
- Lead ontology development, knowledge graph design, semantic interoperability, and AI-ready knowledge representation.
Mission
- Build the semantic foundation for AI reasoning across discovery, preclinical, clinical, and post-marketing domains while preserving meaning, provenance, and translational fidelity.
Key Responsibilities
- Semantic Architecture & Knowledge Modeling: Design/maintain enterprise knowledge models (discovery biology, toxicology, safety pharmacology, pathology, clinical development, pharmacovigilance, real-world evidence); create conceptual/logical/physical knowledge models.
- Ontology Engineering & Governance: Lead ontology strategy, development, governance, lifecycle management; ensure semantic consistency, provenance/traceability, FAIR principles.
- Knowledge Graph & Reasoning Infrastructure: Build RDF-based knowledge graphs; develop mappings/inference rules/reasoning frameworks; enable GraphRAG, semantic retrieval, AI agents; establish interoperability.
- Translational Data Harmonization: Create semantic bridges across SEND, SDTM, ADaM, MedDRA, HPO, MONDO, SNOMED CT, FHIR, OMOP, Cell Ontology, Protein Ontology.
- Scientific & Cross-Functional Leadership: Partner with translational, safety, data science, AI/platform teams; influence semantic strategy and standards communities.
Required Qualifications
- PhD or Master’s in Biomedical Informatics/Bioinformatics/Computational Biology/Computer Science/Information Science/Knowledge Engineering or related.
- 5+ years in biomedical informatics, semantic technologies, knowledge engineering, or scientific data architecture.
- Experience designing ontology-driven knowledge systems across drug discovery/development phases.
- Expertise: ontology governance, knowledge representation; RDF/OWL/SHACL/SPARQL; semantic web technologies.
Preferred Qualifications
- Experience building semantic foundations for AI/GraphRAG/agentic AI/scientific reasoning; LLM-based retrieval/reasoning.
- Contributions to ontology standards/open-source biomedical ontologies/knowledge graphs.
Benefits (time off)
- Vacation 120 hrs/yr; Sick time 40 hrs/yr (Colorado 48; Washington 56); Holiday pay incl. floating holidays 13 days/yr; Parental leave 480 hrs; plus other listed leave time.
- Design and implement semantic and knowledge architecture enabling AI-driven reasoning across the drug discovery and development lifecycle.
- Lead ontology development, knowledge graph design, semantic interoperability, and AI-ready knowledge representation.
Mission
- Build the semantic foundation for AI reasoning across discovery, preclinical, clinical, and post-marketing domains while preserving meaning, provenance, and translational fidelity.
Key Responsibilities
- Semantic Architecture & Knowledge Modeling: Design/maintain enterprise knowledge models (discovery biology, toxicology, safety pharmacology, pathology, clinical development, pharmacovigilance, real-world evidence); create conceptual/logical/physical knowledge models.
- Ontology Engineering & Governance: Lead ontology strategy, development, governance, lifecycle management; ensure semantic consistency, provenance/traceability, FAIR principles.
- Knowledge Graph & Reasoning Infrastructure: Build RDF-based knowledge graphs; develop mappings/inference rules/reasoning frameworks; enable GraphRAG, semantic retrieval, AI agents; establish interoperability.
- Translational Data Harmonization: Create semantic bridges across SEND, SDTM, ADaM, MedDRA, HPO, MONDO, SNOMED CT, FHIR, OMOP, Cell Ontology, Protein Ontology.
- Scientific & Cross-Functional Leadership: Partner with translational, safety, data science, AI/platform teams; influence semantic strategy and standards communities.
Required Qualifications
- PhD or Master’s in Biomedical Informatics/Bioinformatics/Computational Biology/Computer Science/Information Science/Knowledge Engineering or related.
- 5+ years in biomedical informatics, semantic technologies, knowledge engineering, or scientific data architecture.
- Experience designing ontology-driven knowledge systems across drug discovery/development phases.
- Expertise: ontology governance, knowledge representation; RDF/OWL/SHACL/SPARQL; semantic web technologies.
Preferred Qualifications
- Experience building semantic foundations for AI/GraphRAG/agentic AI/scientific reasoning; LLM-based retrieval/reasoning.
- Contributions to ontology standards/open-source biomedical ontologies/knowledge graphs.
Benefits (time off)
- Vacation 120 hrs/yr; Sick time 40 hrs/yr (Colorado 48; Washington 56); Holiday pay incl. floating holidays 13 days/yr; Parental leave 480 hrs; plus other listed leave time.