Principal Scientist – R&D DSDH Ontology Developer TDS Therapeutics Development & Supply (TDS) Full-time

Principal Scientist – R&D DSDH Ontology Developer TDS Therapeutics Development & Supply (TDS)

Johnson & Johnson Innovative Medicine is recruiting for Principal Scientist – R&D DSDH Ontology Developer TDS to design, build, and govern the semantic frameworks that unify data across the development-to-delivery lifecycle for Therapeutics Development & Supply (TDS). You will translate scientific, technical, and operational concepts into well-structured ontologies, controlled vocabularies, and semantic models that enable interoperability, analytics, automation, and AI/ML applications across TDS.

This role combines hands-on ontology engineering with product-oriented thinking, partnering closely with domain experts in Process Development, Manufacturing, Quality, Supply Chain, and Data Science teams. You will serve as a key technical contributor and creative problem solver with a strong understanding of semantic technologies and data modeling in life sciences or manufacturing domains.

Key Responsibilities

• Model, code, test, and publish ontology modules and controlled vocabularies supporting our TDS data ecosystems (e.g., process development, material attributes, equipment hierarchies, batch and product genealogy, quality signals, supply chain flows).
• Translate domain knowledge from SMEs into OWL/RDF classes and properties, SKOS vocabularies, and SHACL constraints, following patterns from established ontology engineering practices.
• Produce validated, versioned semantic models and API-ready outputs for integration into enterprise platforms.
• Build mappings to enterprise canonical models, regulatory standards, and cross-functional ontologies.

Governance, Standards & Quality

• Maintain accountability for components of the TDS ontology roadmap—setting scope, priority, use cases, and success metrics.
• Define and enforce modeling guidelines, naming and versioning conventions, change control processes, and release/deprecation rules, similar to R&D ontology governance frameworks.
• Implement data quality checks including coverage, conformance, identifier normalization, and provenance capture.
• Produce automated validation reports and maintain SPARQL queries/tests.

Integration with Data Products, Analytics & AI/ML

• Ensure TDS ontologies serve as foundational assets enabling knowledge graphs, data products, advanced analytics, and AI/ML workflows—mirroring the AI-readiness focus in technical roles.
• Partner with Data Engineering and Data Architecture teams to embed semantic layers into data pipelines and metadata systems.
• Support automation of classification, normalization, and entity linking using ML/NLP techniques.

Collaboration & Cross-Functional Engagement

• Work with SMEs across Process Development, Manufacturing, Quality, Supply Chain, and Digital/Data Science to capture domain semantics and validate ontology structures.
• Participate in broader enterprise communities of practice advancing data standardization, interoperability, and ontology reuse.
• Engage stakeholders to understand business needs, communicate semantic designs, and ensure fit-for-purpose delivery—reflecting cross-functional expectations in data strategy roles.

Qualifications

Required

• Master's degree or Ph.D. in Life Sciences, Engineering, Computer Science, Mathematics, or related field.
• 3–5+ years of hands-on experience in ontology engineering, knowledge modeling, semantic standards, or knowledge graph development, consistent with expectations in semantic technology roles.
• Proficiency with OWL, RDF(S), SKOS, SHACL, SPARQL, ontology design patterns, and reasoning workflows.
• Experience with graph databases (e.g., Neo4j, GraphDB, etc).
• Strong skills in analytical problem solving, requirements gathering, and translating discussions with SMEs into semantic structures.
• Demonstrated ability to manage multiple projects simultaneously and deliver high-quality outcomes.

Preferred

• Experience with biopharmaceutical development, GMP manufacturing, quality systems, or supply chain data.
• Familiarity with standards such as ISA-88/95, GS1, HL7/FHIR, or manufacturing-oriented ontologies.
• Familiarity with ML/NLP techniques for metadata extraction, classification, or ontology enrichment.
• Understanding of enterprise data platforms, metadata systems, and knowledge graph architectures.

Why This Role Is Unique

This is a rare opportunity to grow in one of the world's most ambitious and fastest-growing Pharma R&D Data Science organizations, shaping how TDS data powers next-generation therapies in the largest biomedical company on the planet. Your work will directly accelerate Johnson & Johnson's scientific discovery, fuel AI innovation, and impact patients globally.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.