Ontologist
Hybrid · Warsaw, Mazovia, Poland
Job Summary
Ontologist at AstraZeneca responsible for designing, building, and evolving the semantic layer to connect and contextualise medical data across the organisation. Collaborates with Medical, Data, Digital, and technical teams to develop ontologies, knowledge graphs, and AZ semantic standards for consistent interpretation, integration, and reuse of data at scale; supports enterprise-wide analytics, AI applications, governance, and compliant data interoperability across markets and therapeutic areas. Hybrid model in Warsaw: 3 days per week in the office.
Required Qualifications
- Bachelor's or Master's degree in Information Science, Computer Science, Bioinformatics, Data Science, Life Sciences, or a related field — or equivalent professional experience
- Demonstrable experience in ontology development, taxonomy design, or semantic data modelling, with evidence of contributing to or leading deliverables within a team setting
- Experience developing ontologies, taxonomies, controlled vocabularies, or knowledge graphs within a structured delivery environment
- Semantic technologies: Working knowledge of RDF, OWL, SKOS, SPARQL, and graph-based knowledge representation
- Data interoperability: Experience using semantic models to integrate and standardise data across multiple systems and sources
- Stakeholder engagement: Ability to work across multiple stakeholder groups including architecture teams, business users/consumers, and governance/assurance functions
- Domain knowledge: Understanding of pharmaceutical, clinical, scientific, or healthcare data domains — particularly where medical and commercial data intersect
- Governance and standards: Experience applying data standards, controlled terminology, and governance practices to improve consistency and reuse
- Communication: Ability to translate business needs into clear semantic solutions and explain ontology concepts to non-technical audiences
- Ways of working: Experience working within multidisciplinary teams in agile or iterative delivery environments
- Industry experience: Experience working in pharmaceutical, biotech, or life sciences environments across medical and/or commercial functions
- Tools: Familiarity with Protégé, TopBraid, Metaphactory, PoolParty, Stardog, Neo4j, Veeva Vault/CRM metadata, Informatica, or Collibra
- Standards: Exposure to terminologies such as SNOMED CT, MedDRA, LOINC, ICD, MeSH, ATC, WHO-DD, or CDISC
- AI and analytics: Understanding of how ontologies and semantic layers support analytics, search, and AI use cases
- Data architecture: Familiarity with enterprise data platforms, metadata management, and data architecture principles
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