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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Scientist, Data Science (Translational... - **Company:** Johnson & Johnson - **Location:** Cambridge, MA, United States - **Experience:** Expert - **Salary:** $117,000.0 - $201,250.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Bioinformatics, Health Informatics, Computational Biology, Data Architecture, Graph Database, Information Sciences, Knowledge-Based Systems, Open Source Technology, Semantic Web, SPARQL, Large Language Models, Knowledge Representation, Information Technology, Virtual Agents - **Published:** July 18, 2026 - **Apply:** https://www.juju.com/job/00000000ghibyj ## About the Role + PhD or Master's degree in: + Biomedical Informatics + Bioinformatics + Computational Biology + Computer Science + Information Science + Knowledge Engineering + Related scientific discipline Experience + 5+ years of experience in biomedical informatics, semantic technologies, knowledge engineering, or scientific data architecture. + Demonstrated experience designing ontology-driven knowledge systems in life sciences, healthcare, or pharmaceutical R&D environments. + Experience working across multiple phases of drug discovery and development. Technical Expertise Deep expertise in: + Ontology development and governance + Knowledge representation + RDF + OWL + SHACL + SPARQL + Semantic Web technologies Strong experience with: + Enterprise ontology management platforms + RDF graph architectures + Semantic APIs + FAIR data principles, + Experience building semantic foundations for AI, GraphRAG, agentic AI, or scientific reasoning systems. + Familiarity with LLM-based retrieval and reasoning architectures. + Experience supporting translational safety, efficacy, biomarker, or mechanistic reasoning use cases. + Contributions to ontology standards, open-source biomedical ontologies, or scientific knowledge graph initiatives. Leadership Competencies + Strategic thinker capable of translating scientific challenges into scalable knowledge architectures. + Strong communicator who can engage effectively with scientists, clinicians, data scientists, engineers, and senior leadership. + Ability to operate in ambiguous, highly cross-functional environments. + Passion for advancing AI-enabled drug discovery and development through semantic and knowledge-driven approaches. ## Description The Principal Translational Knowledge Architect & Graph Lead will be responsible for designing and implementing the semantic and knowledge architecture that enables AI-driven reasoning across the drug discovery and development lifecycle. This role will serve as the scientific and technical lead for ontology development, knowledge graph design, semantic interoperability, and AI-ready knowledge representation. Working at the intersection of translational science, patient safety, biomedical informatics, and artificial intelligence, this individual will help establish the **semantic foundation** required to connect discovery biology, preclinical safety, clinical development, real-world evidence, and post-marketing safety into a unified reasoning framework. The successful candidate will partner closely with scientists, safety experts, data scientists, AI engineers, and platform teams to create knowledge assets that support GraphRAG, agentic AI, scientific reasoning, and next-generation translational intelligence capabilities. Mission Build the semantic foundation that enables AI systems to reason across discovery, preclinical, clinical, and post-marketing domains while preserving scientific meaning, provenance, and translational fidelity. ## Related Videos - [WebMCP - Making Agents a First-Class Citizen of the Web - Andre Cipriani Bandarra & François Beaufort](https://www.wearedevelopers.com/videos/1811-webmcp-making-agents-a-first-class-citizen-of-the-web-andre-cipriani-bandarra-francois-beaufort) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [GraphQL Mesh – Why GraphQL between services is the worst idea and the best idea at the same time!](https://www.wearedevelopers.com/videos/9-graphql-mesh-why-graphql-between-services-is-the-worst-idea-and-the-best-idea-at-the-same-time) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) - [Using all the HTML, Running State of the Browser and "Modern" is Rubbish](https://www.wearedevelopers.com/videos/1291-using-all-the-html-running-state-of-the-browser-and-modern-is-rubbish) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)