Role summary

We are looking for an experienced Ontologist to standardize, extend and build reusable ontologies for the supply chain domain. You will turn existing semantic assets into a coherent, modular, standards-compliant RDF ontology that acts as the authoritative model for our supply chain knowledge graph and enables a supply chain knowledge-graph-as-a-service offering.

Context A significant body of material already exists: domain documentation, Pharma Operations Reference Model (core and domain ontologies, including supply chain) and an operational supply chain graph in Neo4j. The current ontologies are need to be extended and need to consolidate the graph database model. This role closes that gap, so that:

- A reusable ontology, in RDF, drives the knowledge graph database model.
- Gaps in the existing ontologies are identified and filled, so the ontology can serve as the foundation for building an enterprise-grade supply chain knowledge graph.

All modelling must follow both enterprise and domain information and modelling standards, extending shared enterprise and domain ontologies and controlled vocabularies rather than duplicating them.

Key responsibilities

- Review and assess the existing supply chain ontologies, vocabularies and related materials; produce a gap analysis against business needs and enterprise standards.
- Run structured interviews and workshops with subject matter experts to elicit, document and prioritise competency questions, and use them to scope and validate the ontology.
- Design and build a modular, reusable RDF ontology (RDFS/OWL as appropriate) that aligns with and extends enterprise and domain reference models.




- Create and test SHACL shapes that define data constraints and validation rules, keeping a clear separation between semantic definitions and validation.
- Develop controlled vocabularies in SKOS following the enterprise process and standard, reusing enterprise vocabularies wherever possible.
- Verify the ontology fitness for purpose against competency questions and the value the use-case is to deliver to business (e.g. through SPARQL queries and test data).
- Work closely with the graph database engineering team, providing the ontology and shapes as the specification that drives the graph database model. Agree how the ontology maps to the implemented graph database and how changes are kept in sync.
- Enable application and usage of ontologies and vocabularies to enable data, tool and platform interoperability, and to provide semantic context for AI applications (e.g. retrieval, grounding and agent use cases).
- Follow enterprise and domain governance, versioning and release processes. Document design decisions, modelling patterns, and usage guidance so that the assets can be maintained and reused after the engagement.
- Share knowledge with internal teams and contribute to modelling standards and best practice.

Expected deliverables (first 6 months)
- Gap analysis of existing ontologies and materials, with a prioritised remediation plan.




- Agreed and documented set of competency questions, signed off by SMEs.
- Modular supply chain ontology in RDF, aligned to enterprise standards and released through the governed route to live.
- SHACL shapes and SKOS controlled vocabularies supporting the ontology.
- Test suite validating the ontology against the competency questions.
- Agreed ontology-to-graph alignment approach with the graph database engineering team.
- Documentation and handover materials.

Essential skills and experience
- Strong, hands-on RDF modelling and ontology engineering skills, including RDF and appropriate use of OWL.
- Strong SHACL shapes creation and testing skills.
- Practical SPARQL skills.
- Proven ontology development methodology: competency question elicitation and establishment, SME interviews, and translation of business language into clear models.
- Experience designing modular ontologies that maximise reuse, alignment and maintainability of semantic assets.
- Practical experience creating and maintaining controlled vocabularies in SKOS.
- Hands-on experience with tools such as Metaphactory, Progress Semaphore or Protégé.
- Understanding of how ontologies and vocabularies enable data, tool and platform interoperability.
- Proven track record of delivering fit-for-purpose ontologies that have been adopted and applied in practice (please provide examples).
- Understanding of and experience with using ontologies and vocabularies to contextualise data for AI applications.
- Ability to work within enterprise information and modelling standards.
- Transparent communication with technical and non-technical stakeholders.

📌 Ontologist: Supply Chain Semantic Assets (Contract) (India)
🏢 Intuition IT – intuitive technology recruitment
📍 India