Pharma Business Transformation SME – Data Ontology & Knowledge Graph

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.