Principal Data Scientist - Oncology

Principal Data Scientist - Oncology

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 Med Tech, 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.

Job Category:
Data Science (Scientific/Technology). All Job Posting Locations:
Spring House, PA (preferred), Cambridge, MA, San Diego, CA (La Jolla), Titusville, NJ, and Raritan, NJ. No remote option.

• Be a key contributor to the design and implementation of a scalable knowledge graph infrastructure focused on data standardization and interoperability, focusing on Oncology R&D data.
• Apply graph-based data modeling for efficient Oncology R&D organization, integration and retrieval to ensure system flexibility and long‑term maintainability.
• Work with a larger community of Data Scientists, Clinical Scientists and Discovery Scientists to standardize, curate and create AI‑Ready datasets.
• Curate and extend ontologies for clear mapping into established biomedical ontologies and controlled terminologies using RDF standards.
• Work with SPARQL/Graph
  
  QL/REST services; develop ingestion and curation pipelines to ingest, normalize and map concepts across data sources.
• Extend and curate Oncology R&D‑relevant ontologies (e.g., diseases, drugs, targets, pathways, etc.) and maintain synonyms, cross‑references and provenance.
• Partner with cross‑functional teams to enable NLP/RAG over graphs, features for predictive modeling and terminology services for search and study‑design tools.
• Work with Data Science & Digital Health colleagues, IT and Dev Ops teams to deploy and manage the graph database infrastructure, focusing on high availability, scalability and recovery operations specifically geared toward Oncology R&D needs and applications.
• Draft and manage documentation, such as data dictionaries, data lineage and data‑flow diagrams, to facilitate understanding of the knowledge graph.

• Desired Ph.D. or Master’s degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics or related fields, with an emphasis on semantic technologies for biomedical application.
• 5+ years of professional experience in health informatics.
• Demonstrated experience in large‑scale knowledge‑graph construction, ontology development, pharmaceutical or healthcare domain integration.
• Programming background in parser combinators, natural language processing and linked data (RDF triple stores and property graphs).
• Proficiency in semantic web technologies (e.g., SPARQL, RDF, OWL), familiarity with graph databases (Neo4j, Amazon Neptune).
• Proven work with complex biomedical datasets (e.g., clinical, genomics, proteomics).
• Proficiency in various data‑storage solutions (SQL, key‑value, column, document, graph stores) and data‑modeling techniques (semantic data, ontologies, taxonomies).
• Experience in CI/CD implementations, git usage, CI/CD stacks (Jenkins, Git Lab, Azure Dev Ops), Dev Ops tools, metrics/monitoring and containerization technologies (Docker, Singularity).
• Demonstrated stakeholder‑management capabilities—including requirements gathering, business analysis and planning.
• Capacity to translate discussions into user requirements and project plans.
• Ability to manage numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Willingness to conduct periodic travel (