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.

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Data Analytics & Computational Sciences

Data Science

Scientific/Technology

Cambridge, MA;
Raritan, NJ;
San Diego, CA;
Spring House, PA;
Titusville, NJ

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.

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Johnson & Johnson Innovative Medicine is recruiting for a Principal Data Scientist – Oncology to join our Data Science and Digital Health team (DSDH). This position will be located at one of our offices in either Spring House, PA (preferred), Cambridge, MA, or San Diego, CA (La Jolla area). Consideration may be given for our Titusville and Raritan, NJ locations.

The Principal Data Scientist – Oncology will play a pivotal role to standardize and connect biomedical and clinical data. You will be a hands‑on technical contributor with depth in semantic technologies, ontology, and graph data modeling, and strong familiarity with the life sciences domain.

You will connect enterprise master data with R&D data across the entire product lifecycle so trusted, interoperable knowledge powers analytics, search, and AI across Johnson & Johnson Innovative Medicine.

• 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/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, emphasis on semantic technologies for biomedical application.
• 5+ years professional experience in health informatics.
• Demonstrated experience in large‑scale knowledge graphs construction, ontology…