Principal Scientist, R&D Data, Data Science & Artificial Intelligence - Immunology

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld 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.

Learn more at

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.

• 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. Learn more at

The Principal Scientist will be instrumental in contributing to the design, evaluation, and execution of Data Science, Digital Health & AI (DDSAI) strategies in alignment with Immunology Therapeutic Area (IMM TA) priorities and objectives. They will partner with DDSAI colleagues and IMM TA stakeholders to identify, prioritize, and advance data science, digital health, AI, and technology-enabled opportunities across the portfolio. This role helps translate emerging capabilities into practical solutions that improve decision making, research execution, and development outcomes.

To successfully meet these objectives, this individual will work closely with clinical project teams and functional partners across Translational Science, Translational Medicine, Discovery, Late Development, Market Access, Medical Affairs, Data Platforms, Insights & Analytics, and other relevant functions.

• Contribute scientific and strategic input to Immunology R&D DDSAI priorities spanning individual projects, portfolio initiatives, and collaborations with internal and external partners.
• Partner with DDSAI colleagues and Therapeutic Area teams to define, evaluate, and execute high-impact data science, digital health, AI, and analytics initiatives aligned with Immunology R&D objectives.
• Collaborate with Therapeutic Area teams, DDSAI Data Platform teams, Insights & Analytics, and other DDSAI functions to design and implement data science use cases, develop roadmaps from pilot to scale, and identify opportunities for reusable capabilities and workflow standardization.
• Develop a deep understanding of imaging, digital health, clinical, and real-world data assets and align scientific use cases with appropriate datasets, technologies, and partners.
• Map and analyze scientific and operational workflows to identify process improvements, automation opportunities, and future-state solutions that enhance research execution.
• Partner with platform and engineering teams to shape scalable data, analytics, and digital capabilities that are reusable, governed, interoperable, and sustainable.
• Evaluate and pilot emerging technologies, including generative AI, agentic workflows, workflow automation, and advanced analytics, to assess potential impact on Immunology R&D.
• Contribute to data innovation and portfolio intelligence activities by identifying emerging technologies, data assets, and capability opportunities that may enhance R&D decision making.
• Perform detailed analyses, develop high-quality materials, and communicate recommendations in technical and leadership forums to support decision making.
• Other responsibilities in support of DDSAI objectives and broader R&D priorities, as required.

• Masters degree in engineering, mathematics, or a related scientific discipline with at least 4 years of relevant experience. (PhD is a plus.)
• At least 4 years of relevant professional or academic experience in pharmaceutical R&D, biotechnology, healthcare, data science, digital health, AI, analytics, or a related field.
• Demonstrated ability to work effectively in cross-functional and matrixed environments.
• Experience translating scientific or business needs into practical data, analytics, digital health, or AI-enabled solutions.
• Demonstrated experience assessing and applying emerging AI technologies, including generative AI and agentic systems, to address scientific, clinical,…