Director, Early Development Lead, Solid Tumor Oncology, Data Science and 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 Portfolio Management

Job Category:

Professional

All Job Posting Locations:

Horsham, Pennsylvania, United States of America, New Brunswick, New Jersey, 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:

About Innovative Medicine

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 Director, Early Development Lead, Solid Tumor Oncology, Data Science and Digital Health to join the J&J Research and Development Data Science and Digital Health team. You will report to the Head of Solid Tumor Oncology, Data Sciences.

The primary location for this position is either Titusville, NJ, Raritan, NJ, San Diego, CA, Springhouse, PA, New Brunswick, NJ; or Boston, MA. Consideration will be given to other J&J locations. This position may require up to 15% travel.

Key Responsibilities:

• Serve as primary business leader for Data Science & Digital Health for early stage development programs for robust Solid Tumor Oncology portfolio.

• Work with multifunctional clinical teams (e.g. Study physician, translational research, regulatory affairs, CDx) to identify and implement end to end Data Science solutions aimed at facilitating decision making. (e.g. study design, execution, diagnostic planning and strategy)

• Orchestrate and drive solutions with matrixed teams, including technical Data Science teams (e.g. RWD, AI/ML, Omics). This will include the evaluation and development of external partnerships that can leverage new technologies/solutions for clinical trials.

• Establish and maintain new strategic relationships across the Oncology Solid Tumor Early Development programs.

• Provide leadership for Oncology Data Science & Digital Health on investments, strategy and future business planning.

Qualifications

• Ph.D., M.D., or Masters Degree in Medicine, Biotechnology, Statistics, Machine Learning & Artificial Intelligence, Genetics, Physics, Mathematics, Computational Chemistry, Computational Biology, Biology or a related field.

• A minimum of 5 years experience in drug development or related discipline in the field of biotechnology, artificial intelligence, omics, or real-world evidence, or 8 years in clinical practice with outcomes research experience.

• Working knowledge of clinical oncology, such as treatment paradigms, patient experience, and clinical trials

• Familiarity with healthcare relevant datasets, such as EHR, insurance claims or registry data

• Prior experience working and driving external partnerships, either corporate or academic

• Consistent track record of managing timelines and driving key results in a complex organization

• Excellent communication, interpersonal, and written skills

Preferred:

• Hematology/ Oncology fellowship training

• R&D experience at a pharmaceutical company, biotech or partner organization

• Significant experience in translational research, omics, or AI/ML

• An understanding of common data science research practices, such as predictive technologies, data mining and/or text mining

• Hands-on experience with a range of data science use cases in