Lead Ontologist — Pharma R&D
Location: India
Level: Lead / Principal (senior individual contributor with strong influence)
Mandatory Skills : RDF, RDFS, OWL
About the Role
Tech Mahindra is hiring a Lead Ontologist to drive the semantic and knowledge-graph foundations underpinning Pharma R&D's FAIR data and AI strategy. This is a hands-on leadership role: you'll set the ontology vision, define standards, mentor others, and partner directly with R&D scientists, data engineers, and AI/ML teams to make research and CMC/Labs data interoperable, machine-readable, and AI-ready.
You won't just build ontologies — you'll drive the semantic roadmap, influence enterprise architecture decisions, and embed semantic best practice across teams.
What You'll Do
- Own and drive the ontology and knowledge-graph strategy across R&D - CMC & Labs domains.
- Design, govern, and evolve ontologies, taxonomies, and controlled vocabularies using W3C standards.
- Lead integration of LIMS, ELN, CDS, and instrument data into FAIR knowledge graphs.
- Set semantic standards, governance, and versioning; mentor engineers and junior data/semantic practitioners.
- Enable AI/ML and GraphRAG / LLM-plus-knowledge-graph use cases with ontology-backed context.
- Represent client in industry consortia (Allotrope, Pistoia Alliance) and influence external standards.
Mandatory Skills & Experience
- 10+ years overall in data / information / knowledge engineering, of which 4+ years hands-on building and governing ontologies, taxonomies, or knowledge graphs (we value depth and impact over title longevity).
- Demonstrated Lead/Principal-level ownership — driving a semantic, knowledge-graph, or enterprise data-modelling initiative end-to-end, including stakeholder influence and mentoring.
- Strong command of semantic-web standards: RDF, RDFS, OWL, SKOS, SHACL, SPARQL.
- Hands-on ontology development with Protégé (or TopBraid / equivalent).
- Practical experience with a triplestore / graph database (Stardog, GraphDB, AWS Neptune, or Neo4j).
- Solid data modelling, metadata management, and master/reference data foundations, with applied FAIR data knowledge.
- Life-sciences / pharma domain data experience (R&D, drug discovery, CMC, analytical, clinical, or biomedical data) — through ontology work or adjacent roles such as data architecture, cheminformatics/bioinformatics, or scientific data management.
- Proven ability to translate complex science into formal models and to influence and align technical and scientific stakeholders.
Note on background: We welcome candidates who have grown into ontology work from related disciplines — cheminformatics, bioinformatics, taxonomy/library science, data architecture, MDM, or scientific informatics — provided they bring clear, current hands-on semantic delivery.
Preferred Skills
- Familiarity with lab-data standards: Allotrope (AFO/ADF), AnIML, SiLA.
- Knowledge of life-science/chemistry vocabularies: ChEBI, NCIt, UNII, QUDT, InChI/SMILES.
- Python for semantic automation (RDFLib, owlready2, pySHACL).
- Awareness of regulatory & data standards (IDMP, CDISC) and GxP / data integrity.
- Experience embedding ontologies into AI/ML or GraphRAG pipelines.
- Active participation in Allotrope / Pistoia Alliance / W3C standards work
