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Johnson & Johnson

Makes prescription drugs and medical devices

Senior Ontologist - Biologics Discovery

Data ManagementConfirmed live in the last 24 hours
Full-timeMadrid, Spain

About the Job

Requirements

  • An advanced degree in Biomedical Informatics, Computational Biology, Bioinformatics, Data Science, Computer Science, or a related field is required.
  • At least 3 years of experience in ontology engineering, knowledge modeling, taxonomy design, semantic standards, or knowledge graph development is required.
  • Hands-on experience with versioning, change management, validation, and release workflows for ontology assets is required.
  • Proficiency with OWL, RDF(S), SKOS, SHACL, SPARQL, and ontology design patterns is required.
  • Experience with graph and semantic technologies such as Neo4j, GraphDB, Amazon Neptune, Stardog, Protégé, or RDF triple stores is required.
  • Ability to translate scientific discussions into semantic models, validation tests, and delivery plans, and to align semantics across teams and partner organizations is required.
  • Strong communication and cross-functional collaboration skills in a matrixed research and development environment are required.
  • Working knowledge of how ontologies and knowledge graphs ground artificial intelligence and agentic retrieval, such as semantic search, retrieval-augmented generation, or GraphRAG approaches, is required.

Responsibilities

  • Model, code, test, and release validated, versioned ontology modules, controlled vocabularies, and mappings across biologics discovery domains, including antibody and protein engineering, assay metadata, molecular design, profiling, automation outputs, sequence and construct knowledge, and developability signals.
  • Publish ontology packages as API-ready semantic assets consumable by knowledge graphs, data products, and artificial intelligence and machine learning workflows.
  • Partner with biologists, assay scientists, automation teams, and other domain experts to elicit, refine, and translate scientific concepts into computable semantic models while balancing scientific accuracy with practical usability and adoption.
  • Express scientific and operational concepts as OWL/RDF classes and properties, SKOS vocabularies, SHACL constraints, and reusable design patterns, and establish semantic standards adopted across the team's data products.
  • Partner with data engineers to embed semantic layers into data pipelines, catalogs, and knowledge graph platforms.
  • Model scientific entities and concepts as well as processes, workflows, experimental activities, and decision points that generate and govern them, providing context for interoperability, provenance, and reuse.
  • Enable entity linking, classification, normalization, provenance capture, and semantic search across biologics datasets, and ground agentic artificial intelligence and retrieval workflows, including knowledge graph and GraphRAG approaches, so agents can navigate, interpret, and act on scientific data.
  • Build and maintain semantic queries such as SPARQL and automated validation measuring semantic coverage, conformance, lineage, and completeness.
  • Own semantic alignment with enterprise data governance and knowledge graph standards so Biologics Discovery builds on shared enterprise assets rather than duplicating governance.
  • Harmonize terminology and models with peer ontologists supporting downstream development in Chemistry, Manufacturing, and Controls across process, manufacturing, quality, and product lifecycle data, ensuring discovery-to-development handoffs remain traceable and interoperable.
  • Drive consensus across scientific, informatics, and data teams on ontology scope, definitions, and adoption, representing Discovery's semantic needs in enterprise forums.
  • Apply modeling guidelines, naming and versioning conventions, change management, deprecation rules, and semantic quality checks aligned with enterprise governance.

Desired Qualifications

  • Experience in biologics, antibody design, protein engineering, assay biology, or high-throughput experimentation.
  • Experience operating in a governed enterprise environment, preferably pharma or biotech, applying FAIR data principles and enabling interoperability across research and development handoffs.
  • Experience integrating ontology assets into data pipelines, knowledge graphs, search, or agentic artificial intelligence and GraphRAG tools.
  • Familiarity with OBO Foundry ontologies, UMLS, GO, ChEBI, UniProt, HL7/FHIR, or CDISC.

About the Company

Johnson & Johnson

Makes prescription drugs and medical devices

Johnson & Johnson develops prescription medicines and makes medical devices for hospitals, and unlike most big drugmakers, it runs both businesses under one roof. In 2015, its Darzalex became the first antibody drug approved for multiple myeloma, a blood cancer. Its medicines treat cancer, immune diseases such as psoriasis, and mental illnesses such as depression, and patented drugs bring in most of its sales. Its MedTech unit makes heart pumps, catheters that treat irregular heartbeats, surgical sutures, and Acuvue contact lenses. It was founded in 1886 to make sterile surgical dressings, is based in New Brunswick, New Jersey, and spun off its consumer brands, such as Tylenol and Band-Aid, as Kenvue in 2023.

Company size
10,001+
Company stage
IPO
Headquarters
New Brunswick, NJ
Founded
1886

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