Senior Ontologist, Biologics Discovery
6084-Janssen Research & Development, LLC Legal Entity
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Benefits offered by this job
Job summary
Johnson & Johnson Innovative Medicine seeks a Senior Ontologist for Biologics Discovery to design, build, and govern semantic models enabling knowledge graphs, data products, and AI/ML across biologics workflows.
You will partner with experimental scientists and data engineers to translate complex biology into computable ontologies and ensure semantic standards align with enterprise governance across the molecule lifecycle.
Qualifications
- Advanced degree in Biomedical Informatics, Computational Biology, Bioinformatics, Data Science, Computer Science, or a related field.
- Three or more years in ontology engineering, knowledge modeling, taxonomy design, semantic standards, or knowledge graph development.
- Hands‑on experience with versioning, change management, validation, and release workflows for ontology assets.
- Proficiency with OWL, RDF(S), SKOS, SHACL, SPARQL, and ontology design patterns.
- Experience with graph/semantic technologies (e.g., Neo4j, GraphDB, Amazon Neptune, Stardog, Protégé, RDF triple stores).
- Ability to translate scientific discussions into semantic models, validation tests, and delivery plans, and to align semantics across teams and partner organizations.
- Strong communication and cross‑functional collaboration skills in a matrixed R&D environment.
- Working knowledge of how ontologies and knowledge graphs ground AI and agentic retrieval (e.g., semantic search, RAG, or GraphRAG approaches).
Responsibilities
- Ontology Design, Release & Standards: 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/construct knowledge, and developability signals.
- Publish ontology packages as API‑ready semantic assets consumable by knowledge graphs, data products, and AI/ML workflows.
- Partner closely with biologists, assay scientists, automation teams, and other domain experts to elicit, refine, and translate complex scientific concepts into computable semantic models, 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 the semantic standards adopted across the team's data products.
- Knowledge Graphs & Semantic Integration: Partner with data engineers to embed semantic layers into data pipelines, catalogs, and knowledge graph platforms.
- Model not only scientific entities and concepts, but also the processes, workflows, experimental activities, and decision points that generate and govern those entities, providing the context necessary for interoperability, provenance, and reuse.
- Enable entity linking, classification, normalization, provenance capture, and semantic search across biologics datasets, and ground agentic AI and retrieval workflows (e.g., knowledge graph and GraphRAG approaches) so agents can reliably navigate, interpret, and act on scientific data.
- Build and maintain semantic queries (e.g., SPARQL) and automated validation measuring semantic coverage, conformance, lineage, and completeness.
- Enterprise & Cross‑Functional Alignment: 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 (CMC) 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 to enterprise governance.
Skills
Education
Tools
Job description
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/.
Data Analytics & Computational Sciences
Data Science
Scientific/Technology
- Beerse, Antwerp, Belgium
- Madrid, Spain
- Raritan, New Jersey, United States of America
- Spring House, Pennsylvania, United States of America
- Titusville, New Jersey, United States of America
Johnson & Johnson Innovative Medicine is seeking a Senior Ontologist dedicated to our Biologics Discovery organization. This is a horizontal, cross‑cutting role that owns the semantic foundation touching every dataset and every team: how antibody, protein engineering, assay, automation, sequence, external partner, and discovery portfolio data are connected, governed, discovered, and reused. You will be a hands‑on ontologist and cross‑functional catalyst, turning complex scientific language into reusable ontologies, controlled vocabularies, mappings, and semantic standards. This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; Beerse, BE, or Madrid, Spain. (No remote option.) Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s).
USA – Requisition Number: R-099961
Spain – Requisition Number: R-100659
Belgium – Requisition Number: R-100662
Biologics data is generated across many systems and teams, often with terminology that differs by source, which limits how well scientists and models can find, compare, and reuse it. This role provides the semantic connective tissue that makes that data computable, interoperable, and AI‑ready across the Discovery portfolio and with CMC partners, aligning to enterprise standards rather than reinventing them, so semantics remain durable as platforms evolve.
As a Senior Ontologist for Biologics Discovery, you will design, build, test, publish, and govern semantic models that enable knowledge graphs, data products, search, analytics, and AI/ML across biologics workflows. You will partner with experimental scientists, computational biologists, data scientists, data engineers, platform teams, and IT to capture domain semantics and translate them into well‑structured ontology modules, and you will set the semantic standards adopted across the team's data products. A core purpose of this work is to make our data agent‑ready: agentic AI systems cannot reliably navigate, interpret, or act on scientific data without the shared vocabularies, relationships, and constraints that ontologies provide. You will build the semantic layer that lets agents ground their reasoning, retrieve the right data, and connect evidence across experiments, turning fragmented data into knowledge that both scientists and AI can act on. You will align biologics semantics to our enterprise semantic and governance standards, and collaborate with peer ontologists supporting Chemistry, Manufacturing, and Controls (CMC) in the Therapeutics Development & Supply organization so Discovery and downstream semantics stay aligned across the molecule lifecycle.
- Ontology Design, Release & Standards: 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/construct knowledge, and developability signals.
- Publish ontology packages as API‑ready semantic assets consumable by knowledge graphs, data products, and AI/ML workflows.
- Partner closely with biologists, assay scientists, automation teams, and other domain experts to elicit, refine, and translate complex scientific concepts into computable semantic models, 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 the semantic standards adopted across the team's data products.
- Knowledge Graphs & Semantic Integration: Partner with data engineers to embed semantic layers into data pipelines, catalogs, and knowledge graph platforms.
- Model not only scientific entities and concepts, but also the processes, workflows, experimental activities, and decision points that generate and govern those entities, providing the context necessary for interoperability, provenance, and reuse.
- Enable entity linking, classification, normalization, provenance capture, and semantic search across biologics datasets, and ground agentic AI and retrieval workflows (e.g., knowledge graph and GraphRAG approaches) so agents can reliably navigate, interpret, and act on scientific data.
- Build and maintain semantic queries (e.g., SPARQL) and automated validation measuring semantic coverage, conformance, lineage, and completeness.
- Enterprise & Cross‑Functional Alignment: 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 (CMC) 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 to enterprise governance.
This is a rare opportunity to define the semantic foundation for Biologics Discovery and to work at one of its most strategic cross‑organizational interfaces: the alignment with enterprise data governance and downstream development partners. You will shape how breakthrough biologics knowledge is captured, connected, governed, and made actionable for scientists and AI systems.
The ideal candidate is a builder, translator, and systems thinker who is knowledgeable about biologics discovery and energized by its potential to impact human health. They can discuss the science fluently with experimental teams, design rigorous semantic models with technical peers, translate complex biology into machine‑readable formats, represent Discovery credibly with enterprise and development partners, and advocate for governance that makes data more reusable without slowing innovation. They are motivated above all by turning connected biologics knowledge into faster, better medicines for patients.
- Advanced degree in Biomedical Informatics, Computational Biology, Bioinformatics, Data Science, Computer Science, or a related field.
- Three or more years in ontology engineering, knowledge modeling, taxonomy design, semantic standards, or knowledge graph development.
- Hands‑on experience with versioning, change management, validation, and release workflows for ontology assets.
- Proficiency with OWL, RDF(S), SKOS, SHACL, SPARQL, and ontology design patterns.
- Experience with graph/semantic technologies (e.g., Neo4j, GraphDB, Amazon Neptune, Stardog, Protégé, RDF triple stores).
- Ability to translate scientific discussions into semantic models, validation tests, and delivery plans, and to align semantics across teams and partner organizations.
- Strong communication and cross‑functional collaboration skills in a matrixed R&D environment.
- Working knowledge of how ontologies and knowledge graphs ground AI and agentic retrieval (e.g., semantic search, RAG, or GraphRAG approaches).
- Biologics, antibody design, protein engineering, assay biology, or high‑throughput experimentation.
- Operating in a governed enterprise environment, preferably pharma or biotech, applying FAIR data principles and enabling interoperability across research and development handoffs.
- Integrating ontology assets into data pipelines, knowledge graphs, search, or agentic AI / GraphRAG tools.
- Familiarity with OBO Foundry ontologies, UMLS, GO, ChEBI, UniProt, HL7/FHIR, or CDISC.
This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ, USA; Beerse, BE, or Madrid, Spain. (No remote option.)
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. If you are under 18 years of age, you (the candidate) may need to obtain the necessary working papers or other documentation required by state law to start the assignment, as well as get a parent’s consent for the background check. Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
The anticipated base pay range for this position is $109,000 to $174,800. The Company maintains highly competitive, performance‑based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation’s performance over a calendar/performance year. Bonuses are awarded at the Company’s discretion on an individual basis.
- Medical
- Dental
- Vision
- Life insurance
- Short‑term disability
- Long‑term disability
- Business accident insurance
- Group legal insurance
- Pension (retirement plan)
- 401(k) (savings plan)
- Vacation – up to 120 hours per calendar year
- Sick time – up to 40 hours per calendar year
- Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time – up to 40 hours per calendar year
Additional information can be found through the link below. https://www.careers.jnj.com/employee-benefits
- Advanced Analytics, Business Intelligence (BI), Coaching, Collaboration, Critical Thinking, Data Analysis, Database Management, Data Privacy Standards, Data Reporting, Data Savvy, Data Science, Data Visualization, Econometric Models, Process Improvements, Technical Credibility, Technologically Savvy, Workflow Analysis
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