Senior Manager, Oncology Data and AI Systems

Overview

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.

Data Analytics & Computational Sciences

Data Science

People Leader

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

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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Johnson & Johnson Innovative Medicine is recruiting for a Senior Manager, Oncology Data and AI Systems to join our Data, Data Science and Artificial Intelligence team (DDSAI). This position will be located on site at one of our offices in either Spring House PA, Cambridge MA, Titusville NJ, Raritan NJ, or San Diego CA (no fully remote option available).

• Serve as both a people leader and a hands-on contributor accountable for the end-to-end design, development, and operation of scalable, AI-enabled data products supporting Oncology R&D.
• Drive integration of diverse data sources (e.g., biomarker labs, real-world data, pre-clinical and translational systems) into high-quality, reusable, AI-ready assets.
• Partner closely with Oncology R&D and Data Science stakeholders to shape, prioritize, and deliver against business-critical use cases. Translate complex scientific and operational needs into robust data products and AI systems that accelerate decision-making, improve study execution, and enhance probability of success.
• Collaborate with domain experts, such as Ontology, Knowledge graph, and Data Product Engineers to design and deliver future-proof, AI-ready data systems aligned with Oncology Strategy. Ensure solutions enable discoverability, reuse, and advanced analytics/GenAI applications.
• Implement standard enterprise-level data models and create new data models as needed.
• Leverage cloud-based technology platforms to accomplish data and AI goals.
• Lead the design and optimization of data pipelines and AI workflows for structured and unstructured data using technologies such as Python, SQL, AWS services and other relevant tools. Mentor and on-board new team members.
• Implement quality and performance standards and measure Key Performance Indicators (KPIs) to determine accuracy and consistency.
• Lead team in the development of Agile practices and agentic AI coding tools.
• Act as a thought leader across Data Science, Engineering, and Oncology domains, ensuring alignment with broader data product strategy and avoiding duplication through reuse and standardization.

• 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).
• 6+ years of experience in data engineering, including data modeling and database design, preferably in the healthcare industry.
• Proficiency in agentic AI coding tools, e.g. Claude Code, Codex, etc.
• Proficiency in data engineering tools such as Python and SQL for data processing as well as cloud architecture (e.g. AWS services, Redshift, FSx, Glue, Lambda).
• Experience with unstructured database technologies (e.g. No
  
  SQL) as well as other database types (e.g. Graph).
• Strong skills in analysis, problem-solving, organizational change, project delivery, and managing external vendors. Proven record leading improvement initiatives with multi-disciplinary and remote partners. Demonstrated stakeholder management capabilities— including requirements gathering, business analysis and planning. Must have the capacity to translate discussions into user requirements and project plans.
• Ability to manage numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
• Willingness to conduct periodic travel (