Principal Data Scientist - Oncology

Job Function

Data Analytics & Computational Sciences

Data Science

Scientific/Technology

Spring House, PA (preferred);
Cambridge, MA;
San Diego, CA (La Jolla area);
Titusville, NJ;
Raritan, NJ.

Johnson & Johnson Innovative Medicine is recruiting for a Principal Data Scientist
- Oncology to join the Data Science and Digital Health team (DSDH). This position will be located in one of the listed locations (Spring House, Cambridge, San Diego; optional Titusville, Raritan). The Principal Data Scientist
- Oncology will play a pivotal role in standardizing and connecting biomedical and clinical data. The role is a hands‑on technical contributor with depth in semantic technologies, ontology, and graph data modeling, and strong familiarity with the life sciences domain.

• 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 resource description framework (RDF) standards.
• Work with SPARQL/GraphQL/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, emphasis on semantic technologies for biomedical application.
• 5+ years professional experience in health informatics.
• Demonstrated experience in large‑scale knowledge graphs construction, ontology development, pharmaceutical or healthcare domains 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. Must have the capacity to translate discussions into user requirements and project plans.
• Ability to manage a numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Willingness to conduct periodic travel (