Principal Scientist - R&D DSDH Ontology Developer TDS Therapeutics Development & Supply; TDS

Principal Data Scientist – Ontology Developer (TDS)
Position Summary

• Design, build, and govern semantic frameworks that unify data across the development-to-delivery lifecycle for Therapeutics Development & Supply (TDS).
• Translate scientific, technical, and operational concepts into ontologies, controlled vocabularies, and semantic models to enable interoperability, analytics, automation, and AI/ML applications.
• Partner with domain experts in Process Development, Manufacturing, Quality, Supply Chain, and Data Science to contribute and solve technical problems in life sciences/manufacturing data modeling.

• Model, code, test, and publish ontology modules and controlled vocabularies for TDS data ecosystems (e.g., process development, material attributes, equipment hierarchies, batch/product genealogy, quality signals, supply chain flows).
• Translate SME knowledge into OWL/RDF, SKOS vocabularies, and SHACL constraints.
• Produce validated, versioned semantic models and API‑ready outputs for enterprise integration.
• Build mappings to enterprise canonical models, regulatory standards, and cross‑functional ontologies.

• Own components of the TDS ontology roadmap (scope, priorities, use cases, success metrics).
• Define/enforce modeling guidelines, naming/versioning conventions, change control, and release/deprecation rules.
• Implement data quality checks (coverage, conformance, identifier normalization, provenance capture).
• Produce automated validation reports and maintain SPARQL queries/tests.

• Enable knowledge graphs, data products, advanced analytics, and AI/ML workflows.
• Embed semantic layers into data pipelines and metadata systems with Data Engineering and Data Architecture teams.
• Support automation of classification, normalization, and entity linking using ML/NLP.

• Work with SMEs to capture domain semantics and validate ontology structures.
• Participate in communities of practice for standardization, interoperability, and ontology reuse.
• Engage stakeholders to understand business needs and ensure fit‑for‑purpose delivery.

• Master’s degree or Ph.D. in Life Sciences, Engineering, Computer Science, Mathematics, or related field.
• 3–5+ years hands‑on ontology engineering/knowledge modeling/semantic standards/knowledge graph development.
• Proficiency with OWL, RDF(S), SKOS, SHACL, SPARQL, ontology design patterns, and reasoning workflows.
• Experience with graph databases (e.g., Neo4j, Graph
  
  DB).
• Strong analytical problem solving and requirements gathering; ability to translate SME discussions into semantic structures.
• Ability to manage multiple projects simultaneously and deliver high‑quality outcomes.

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

• Advanced Analytics, Critical Thinking, Data Analysis, Data Quality, Data Science, Data Reporting, Data Visualization, Digital Fluency, Strategic Thinking, Technical Credibility, Workflow Analysis, Data Privacy Standards, Process Improvements, Organizing, Coaching, Econometric Models.

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• Vacation: 120 hours per calendar year
• Sick time: 40 hours per calendar year (CO: 48; WA: 56)
• Holiday pay (including floating holidays): 13 days per calendar year
• Work, Personal and Family Time: up to 40 hours per calendar year
• Parental Leave: 480 hours within one year of birth/adoption/foster care
• Bereavement Leave: 240 hours for immediate family; 40 hours for extended family per calendar year
• Caregiver Leave: 80 hours in a 52‑week rolling period
• Volunteer Leave: 32 hours per calendar year
• Military Spouse Time‑Off: 80 hours per calendar year