Pharma Business Transformation SME – Data Ontology & Knowledge Graph Location: Remote Experience: 12+ Years Industry: Pharmaceutical / Life Sciences About the Role: We are seeking an experienced Pharma Business Transformation SME with deep expertise in Data Ontology, Semantic Modeling, and Knowledge Graphs to lead the development of an enterprise-wide Pharmaceutical Knowledge Graph. This role will partner with business and technology leaders to create a semantic data foundation that enables AI, advanced analytics, and digital transformation across the pharma value chain. Key Responsibilities: Define and lead enterprise ontology and semantic data strategies. Design pharmaceutical ontologies covering R&D, Clinical, Regulatory, Safety, Manufacturing, Quality, Medical Affairs, and Commercial domains. Build and govern knowledge graphs, taxonomies, vocabularies, and semantic models. Collaborate with business stakeholders, data architects, and AI teams to establish a unified view of enterprise data. Drive adoption of industry standards such as CDISC, MedDRA, FHIR, SNOMED, and IDMP. Enable AI/GenAI, data discovery, interoperability, and decision intelligence through semantic technologies. Establish data governance, stewardship, and ontology management processes. Required Qualifications 12+ years of experience in Pharmaceuticals or Life Sciences. 5+ years of hands-on experience in Ontology Engineering, Semantic Modeling, or Knowledge Graph implementations. Strong understanding of pharmaceutical business processes and data domains. Experience with RDF, OWL, SPARQL, SKOS, and graph technologies. Expertise with platforms such as Neo4j, Stardog, Ontotext, Amazon Neptune, Collibra, or similar. Proven track record leading enterprise data transformation initiatives.

Preferred Qualifications

Experience implementing enterprise knowledge graphs for global pharma organizations. Familiarity with AI/GenAI, Data Fabric, Metadata Management, and Master Data Management (MDM). Advanced degree in Life Sciences, Bioinformatics, Data Science, or Computer Science.