Enterprise Ontologist

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As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

Join our collaborative team as an Enterprise Ontologist and design, develop, and govern the semantic models that power Thermo Fisher's Enterprise Knowledge Graph (EKG) and AI-driven digital experiences. This role translates complex scientific and business domains into scalable knowledge structures that improve search, content discovery, data interoperability, and AI performance.

Working across scientific, Content, Product, AI, Data Science, and Engineering teams, the Enterprise Ontologist will serve as a key steward of the knowledge foundation supporting thermofisher.ai and the Foundry, ensuring enterprise ontologies remain accurate, governed, scalable, and aligned with evolving scientific and business needs.

• Design, develop, and govern enterprise ontologies and semantic models supporting the EKG and enterprise AI applications.
• Model scientific, product, and operational concepts and relationships using enterprise taxonomies, controlled vocabularies, and authoritative external ontologies.
• Partner with scientific SMEs and business and technical teams to translate complex requirements into scalable semantic models.
• Establish ontology governance, including standards, quality assurance, lifecycle management, versioning, provenance, and change management.
• Develop mappings across taxonomies, external ontologies, enterprise data sources, and knowledge graph entities.
• Enable and optimize AI capabilities including semantic search, content classification, RAG, knowledge grounding, and recommendation systems.
• Evaluate ontology effectiveness and identify opportunities to improve retrieval, content quality, knowledge coverage, and AI performance.
• Provide ontology guidance and training to scientific, content, business, and technical stakeholders.

• Bachelor's degree in Life Sciences, Chemistry, Biology, Biochemistry, Bioinformatics, Information Science, Computer Science, Data Science, or a related scientific or technical field. Master's degree preferred.
• 5+ years of experience developing or managing ontologies, semantic data models, taxonomies, knowledge graphs, or information architecture. Experience with scientific or biomedical knowledge models and AI/search applications strongly preferred.

• Expertise in ontology engineering, knowledge representation, semantic modeling, and knowledge graph design, including standards such as OWL, RDF, and SKOS.
• Strong scientific literacy and knowledge of life-science terminology, concepts, techniques, applications, and experimental workflows.
• Ability to translate complex scientific and technical information into scalable semantic models and knowledge structures.
• Familiarity with scientific ontologies, controlled vocabularies, semantic technologies, graph databases (neo4j and PostgresSQL preferred), and ontology management tools.
• Understanding of AI and search technologies, including semantic search, RAG, NLP, knowledge grounding, and LLM-based applications.
• Proven ability to establish ontology governance, quality, lifecycle, and data stewardship practices.
• Str…