Enterprise Ontologist
Thermo Fisher Scientific
Summary
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.
Job description
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.
Key Responsibilities
- 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.
Minimum Education & Experience
- 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.
Required Knowledge or Experience
- 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.
- Strong analytical and systems-thinking skills with the ability to navigate complex scientific and enterprise knowledge domains.
- Excellent communication and collaboration skills, including the ability to work effectively with scientific SMEs and technical and non-technical stakeholders.
- Travel: 10-25%
Requirements
- Bachelor's degree in Life Sciences, Chemistry, Biology, Biochemistry, Bioinformatics, Information Science, Computer Science, Data Science, or a related scientific or technical field
- 5+ years of experience developing or managing ontologies, semantic data models, taxonomies, knowledge graphs, or information architecture
- 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
- Strong analytical and systems-thinking skills with the ability to navigate complex scientific and enterprise knowledge domains
- Excellent communication and collaboration skills, including the ability to work effectively with scientific SMEs and technical and non-technical stakeholders
- Travel: 10-25%
Company overview
Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue of approximately $40 billion. The company's mission is to enable customers to make the world healthier, cleaner, and safer. With over 100,000 employees globally, Thermo Fisher provides an unrivaled combination of innovative technologies, purchasing convenience, and pharmaceutical services through its industry-leading brands including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon, and PPD. The company serves customers across healthcare, life sciences, applied markets, and pharmaceutical sectors, offering solutions that accelerate research, solve complex analytical challenges, improve patient diagnostics, and increase laboratory productivity. Headquartered in Waltham, Massachusetts, Thermo Fisher operates globally, delivering critical scientific products, services, and workflow solutions that support researchers, organizations, and companies in addressing some of the world's most pressing issues.