Find & Apply For Data Scientist Jobs in Spring House, Pennsylvania

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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.

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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.

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//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. 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 and Johnson Innovative Medicine. Primary 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 .

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