Principal Ontologist - R&D DDSAI - Preclinical Sciences & Translational Safety

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Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Beerse, Antwerp, Belgium, Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain, Spring House, Pennsylvania, United States of America

Job Description:

We are seeking a Principal Scientist/Ontologist to join our R&D DDSAI team, dedicated to developing and supporting ontologies, controlled vocabularies, and semantic data standards for PSTS.

This hands-on scientific and technical role will establish consistent terminology across PSTS projects, translate scientific knowledge into reusable semantic models, and strengthen connections between PSTS and other departments across the R&D pipeline. Working closely with scientific subject matter experts, data scientists, data engineers, and technology partners, you will help make scientific data easier to find, understand, integrate, and reuse.

The successful candidate combines expertise in ontology engineering with an understanding of pharmaceutical research and a collaborative approach to solving complex scientific data challenges.

Key Responsibilities

Ontology Creation & Terminology Standardization

• Design, develop, test, and maintain ontology modules and controlled vocabularies supporting PSTS scientific workflows, including toxicology, safety assessment, pharmacokinetics/pharmacodynamics, and translational research.
• Partner with PSTS scientists to capture scientific concepts, definitions, relationships, and experimental context, translating these into well-structured semantic models.
• Harmonize terminology across projects, studies, assays, and data sources while preserving scientifically meaningful distinctions.
• Develop mappings between project-specific terminology, shared R&D ontologies, and relevant external standards, prioritizing reuse over unnecessary duplication.

Project Support & Adoption

• Serve as a primary ontology and terminology resource for PSTS project teams, supporting requirements gathering, semantic annotation, data mapping, and issue resolution.
• Partner with data engineers and platform teams to incorporate ontology terms and mappings into data products, metadata systems, and scientific workflows.
• Provide practical documentation, examples, and training that help scientists and technical teams adopt standardized terminology.
• Maintain a prioritized backlog of ontology enhancements and support requests aligned with PSTS scientific needs.

Cross-R&D Interoperability

• Collaborate with peer ontologists and scientific data teams across discovery, development, therapeutic areas, and other R&D functions.
• Establish shared definitions that connect PSTS evidence with upstream discovery and downstream development data.
• Identify opportunities to reuse ontology components and improve cross-study and cross-functional data integration.

Governance, Quality & Lifecycle Management

• Apply modeling guidelines, naming conventions, persistent identifiers, version control, change management, and release practices.
• Maintain traceable definitions, mappings, provenance, and documentation of modeling decisions.
• Assess the impact of ontology changes on consuming projects and coordinate updates with scientific and technical stakeholders.

Analytics & AI Readiness

• Help ensure PSTS datasets retain the scientific context needed for reliable interpretation and reuse.
• Evaluate approaches to terminology extraction and mapping automation, with appropriate scientific review.

Qualifications

Required

• Master’s degree or Ph.D. in Biomedical Informatics, Bioinformatics, Life Sciences, Engineering, or a related discipline.
• Hands-on experience developing and maintaining ontologies, controlled vocabularies, semantic models, or knowledge graphs for scientific or biomedical applications.
• Experience with ontology development tools (e.g., Protégé, OWL/RDF) version control, and scripting for data transformation and validation.
• Ability to translate scientific requirements into clear, reusable semantic structures.
• Strong communication, problem-solving, and stakeholder engagement skills.
• Ability to manage multiple workstreams and deliver practical solutions in a matrixed environment.

Preferred

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