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 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: Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, San Diego, California, 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

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.

Responsibilities:

• 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 DevOps 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.

Preferred Qualifications:

• Desired Ph.D. or Masters 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, GitLab, Azure DevOps), DevOps tools, metrics/monitoring, and containerization technologies (Docker, Singularity).
• Demonstrated stakeholder management capabilities, including requirements gathering, business analysis, and planning.
• Ability to translate discussions into user requirements and project plans.
• Willingness to conduct periodic travel (<15% of time) to conferences and internal meetings.

Compensation and Benefits:

The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.

Equal Opportunity Employer:

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status, or other characteristics protected by federal, state, or local law.

Job Location:

The 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.

Required Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

Preferred Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis