Manager, Data Science – 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 Med Tech, 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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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 People Leader

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.

Johnson & Johnson Innovative Medicine is recruiting for a Manager, Data Science – 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 Manager, Data Science – Oncology will support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements. This role will focus on applications in Oncology R&D and support data projects from across the business including Clinical, Pre-Clinical, RWD and ‘omics platforms. This role will be a leading technical contributor and creative problem solver with developing AI-ready data and other routinely used data applications for Oncology R&D.

Key Responsibilities

• Serve as both a people leader and a hands‑on contributor for designing, developing and maintaining data pipelines for acquiring, managing and storing Oncology R&D data from diverse sources (e.g. biomarker labs, real‑world data sources, pre‑clinical applications)
• Work closely with Data Science and Oncology R&D partners to understand, document and prioritize business requirements. Translate these business needs into high quality data products.
• Work closely with other technical leaders, such as Ontology and Knowledge graph Engineers to design and deliver future‑proof, AI‑ready data systems aligned with Oncology R&D business needs.
• Develop Oncology R&D‑specific data repositories by implementing standard enterprise‑level data models and create new data models as needed. Leverage cloud‑based technology platform to accomplish goals, such as building and maintaining data repositories using AWS S3.
• Create and optimize data flows for structured and unstructured data using technologies such as Python, R, SQL, AWS services and other relevant tools.
• Implement quality and performance standards and measure KPIs to determine accuracy and consistency.
• Leverage and implement data versioning and lineage tracking to support data traceability, compliance, maintaining documentation for data architectures and workflows.
• In adherence to internal standards, implement software development best practices such as Code Versioning, Dev Ops.

Required Qualifications

• Advanced degree (Master’s or equivalent) in Computer Science, Engineering, Life Sciences, or other relevant field is strongly preferred. (Bachelor’s Degree with experience equivalency may be considered.)
• 5+ years of experience in data engineering,…