Lead Ontologist

Tech Mahindra; Hyderabad; On-site; INR 5,500,000 - 6,500,000; Full time

Job summary

Tech Mahindra is seeking a Lead Ontologist to drive semantic and knowledge-graph foundations for Pharma R&D’s FAIR data and AI strategy. This hands-on leadership role sets ontology vision, standards, and mentors teams to ensure data are interoperable and AI-ready.

You will drive the semantic roadmap, influence enterprise architecture decisions, and embed semantic best practices across teams, ensuring alignment with Allotrope and Pistoia Alliance standards.

Qualifications

• 10+ years in data/information/knowledge engineering.
• 4+ years building ontologies, taxonomies, or knowledge graphs.
• Lead/Principal ownership of semantic or enterprise data modelling initiatives.
• Strong command of semantic-web standards (RDF/RDFS/OWL/SKOS/SHACL/SPARQL).
• Experience with triplestore/graph databases and FAIR data knowledge.

Responsibilities

• Own and drive ontology and knowledge-graph strategy across R&D domains.
• Design and govern ontologies, taxonomies, and controlled vocabularies per standards.
• Lead integration of lab data into FAIR knowledge graphs (LIMS, ELN, CDS).
• Set semantic standards, governance, and versioning; mentor engineers.
• Enable AI/ML and GraphRAG use cases with ontology-backed context.
• Represent client in industry consortia and influence external standards.

Skills

RDF

RDFS

OWL

SKOS

SHACL

SPARQL

Ontology modeling

Knowledge graphs

Tools

Stardog

GraphDB

AWS Neptune

Neo4j

RDFLib

pySHACL

Job description

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.
• 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