Senior Ontologist, Biologics Discovery

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 jnj.com . As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: Scientific/Technology All Job Posting Locations: 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 Job Description: Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine About the opportunity 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 Why this role matters: 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. Position Summary 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. Key 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