Spring House, Pennsylvania, United States of America
Base: $117,000 to $201,250; bonus/equity: eligible...
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Knowledge graph infrastructure
Semantic technologies
Ontology development
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Johnson & Johnson is seeking a Principal Data Scientist specializing in Oncology to join their Data Science and Digital Health team. The ideal candidate will focus on developing a scalable knowledge graph infrastructure to standardize and connect biomedical and clinical data, particularly in Oncology research and development.
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Job Summary
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
The Principal Data Scientist - Oncology, will play a pivotal role to standardize and connect biomedical and clinical data.
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).
Matching Summary
Match Score: 75
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Johnson & Johnson is seeking a Principal Data Scientist specializing in Oncology to join their Data Science and Digital Health team. The ideal candidate will focus on developing a scalable knowledge graph infrastructure to standardize and connect biomedical and clinical data, particularly in Oncology research and development.
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Salary
Base: $117,000 to $201,250; Bonus/Equity: eligible for an annual performance bonus; Benefits: medical, dental, vision, life insurance, disability, retirement plan, savings plan, vacation, sick time, holiday pay, personal and family time
Skills & Requirements
Must-have
knowledge graph infrastructure
semantic technologies
ontology development
graph data modeling
SPARQL/GraphQL/REST services
RDF standards
Nice-to-have
stakeholder management capabilities
translate discussions into requirements
manage numerous projects simultaneously
organizational skills and flexibility
Key Requirements
5+ years professional experience in health informatics
Ph.D. or Master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields
Demonstrated experience in large-scale knowledge graphs construction