Thermo Fisher Scientific

Thermo Fisher Scientific

Posted via Workday

Enterprise Ontologist

Posted Sep 30, 2026

Role at a glance

Job function
AI & Data Other
Salary
Not Disclosed
Location
Remote - Pennsylvania, United States
Work arrangement
Hybrid
Employment
Full-time
Experience
5+ years of experience developing or managing ontologies, semantic data models, taxonomies, knowledge graphs, or information architecture.
Education
Bachelor's degree in Life Sciences, Chemistry, Biology, Biochemistry, Bioinformatics, Information Science, Computer Science, Data...

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Role Summary

AI-generated

The Enterprise Ontologist designs and governs semantic models for Thermo Fisher's Enterprise Knowledge Graph and AI-driven digital experiences. The role works with scientific, content, product, AI, data science, and engineering teams to maintain knowledge structures aligned with scientific and business needs.

What You'll Do

  • Design, develop, and govern enterprise ontologies and semantic models.
  • Model scientific, product, and operational concepts using taxonomies, controlled vocabularies, and external ontologies.
  • Translate scientific, business, and technical requirements into scalable semantic models, and develop mappings across knowledge sources.
  • Establish ontology standards, quality assurance, lifecycle management, versioning, provenance, and change management.
  • Enable and optimize semantic search, content classification, RAG, knowledge grounding, and recommendation systems.
  • Evaluate ontology effectiveness and provide guidance and training to stakeholders.

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Requires expertise in ontology engineering, knowledge representation, semantic modeling, and knowledge graph design, including OWL, RDF, and SKOS. Also requires scientific literacy in life-science terminology and workflows; familiarity with scientific ontologies, controlled vocabularies, semantic technologies, and ontology management tools; understanding of semantic search, RAG, NLP, knowledge grounding, and LLM-based applications; and ability to establish ontology governance and data stewardship practices. Strong analytical, communication, and collaboration skills are required.

Preferred

  • Master's degree.
  • Experience with scientific or biomedical knowledge models and AI/search applications is strongly preferred.
  • Graph databases neo4j and PostgresSQL are preferred.

Original job description

Content provided by the employer

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

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.

Description
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.

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%

Thermo Fisher Scientific

About the company

Thermo Fisher Scientific

Large Enterprise

Thermo Fisher Scientific is a global leader in serving science, providing a wide range of analytical instruments, reagents, and software solutions for healthcare, pharmaceuticals, and life sciences research. With a commitment to innovation and quality, the company enables customers to make significant advancements in scientific discovery and healthcare diagnostics. Thermo Fisher operates in more than 50 countries and employs over 80,000 people, fostering a collaborative environment aimed at enhancing global health and safety. Through its broad portfolio of brands and technologies, the company plays a vital role in accelerating life-changing research and improving patient outcomes worldwide.