Director, Oncology Enterprise Data Science, R&D Oncology Data Science & Digital Health

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 https://www.jnj.com

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

People Leader

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, La Jolla, California, United States of America, New Brunswick, New Jersey, United States of America, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

Johnson and Johnson Innovative Medicine is recruiting for a Director, Oncology Enterprise Data Science to aid design, build, and govern the technology backbone that connects data and delivers AI-based solutions across pharmaceutical life cycle. You’ll translate business needs into a strategy and execution plan for enterprise AI-based solutions for Oncology R&D.   This will include well-formed ontologies, controlled vocabularies, and semantic standards that power interoperability, search and discovery, analytics, and AI/ML.  The role links together business needs with product thinking, partnering closely with governance, knowledge management, and domain stakeholders. You are a leading strategic and tactical contributor and creative problem solver.

The primary location for this position is either New Brunswick, NJ or Spring House, PA, Cambridge, MA, Raritan, NJ and Titusville, NJ, La Jolla, CA or other JRD locations.  

Johnson & Johnson Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, retinal disorders, and neuroscience. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Janssen, one of the Pharmaceutical Companies of Johnson & Johnson, visit https://www.janssen.com/johnson-johnson-innovative-medicine.

Primary Responsibilities

• You will work with Data Science and Oncology R&D business leaders to translate AI-based enterprise business opportunities into hands on research plans. This includes technical execution of AI projects, including study design, technology builds that deliver scientific insights to the Oncology R&D pipeline.
• Deliver AI-solutions across a wide range of data domains for the R&D pipeline, including discovery, translational and clinical trial data.
• Serve as a key contributor to the over-arching enterprise AI strategy and to enable the scaling and deployment of tools aimed at the broader R&D community.
• Work with multidisciplinary teams who will model, code, test, and release ontology modules and mappings that power knowledge graph, master/reference data, analytics, and AI/LLM applications to Oncology R&D Scientists.
• Participate in a wider community of scientists standardizing biomedical data across R&D aimed at increasing AI Readiness and delivering AI solutions across a broad range of data domains
• Evaluate and deliver external partnering opportunities to access cutting edge technologies to apply AI to diverse R&D data sets.

Qualifications:

• Desired Ph.D. or master's degree in bioengineering, computer science, IT, bioinformatics, or related fields, emphasis on technologies and biomedical applications.
• 5+ years of experience delivering data-rich, computational solutions to scientific problems in the healthcare industry.
• Foundational knowledge and experience in machine learning, and AI.  Experience with NLP, LLM, Generative models important.
• Familiarity with foundational technologies required for the execution of AI projects (e.g. git usage