Lead Ontologist

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

Skills Required
Neo4j, Rdf, Sparql, GraphDB, owl, rdfs, Python