Director, Data Science - AI Evidence Extraction

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 jnj.com.

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, 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.

Learn more at https://www.jnj.com/innovative-medicine

Johnson & Johnson Innovative Medicine is recruiting for Director, Data Science – AI Evidence Extraction to join our J&J Research and Development Data, Data Science, and AI (DDSAI) team. This position will be located at one of our US sites (Raritan, NJ; Titusville, NJ; Cambridge, MA; Spring House, PA).

POSITION SUMMARY

The Director will lead the design, development, and deployment of AI-enabled capabilities (e.g., agentic workflows) for scientific evidence extraction, curation, and quantitative synthesis in support of clinical development for Neuroscience R&D. Working closely with clinical, statistical, regulatory, scientific, and data teams, the candidate will translate priority evidence needs into scalable tools and reusable data assets that improve how information from the scientific literature and other sources is identified, structured, evaluated, and analyzed.

This hands-on technical leader will set technical direction, guide multidisciplinary delivery, and build and validate robust evidence workflows. The role will establish fit-for-purpose data models, provenance and quality standards, evaluation and human-review best practices, and scientifically rigorous analytical approaches, while ensuring alignment with enterprise platforms, responsible AI expectations, and data-use requirements. Success will depend on partnering across functions to build workflows, drive their adoption, communicate uncertainty and tradeoffs, and deliver measurable value for clinical development decisions.

Why This Role Is Unique

Most AI systems produce answers that are quickly forgotten. This role will build a curated, provenance-bearing evidence asset that makes each subsequent analysis faster, less costly, and more reliable. The Director will choose evidence domains, ensure compliant data use, and establish standards that other programs can reuse. Success at twelve months means Neuroscience analysts begin meta-analyses by querying this evidence store, reviewers can trace pooled values to their cited source without assistance, and additional therapeutic areas seek to adopt the capability. The work will accelerate Johnson & Johnson's clinical development, advance AI-enabled evidence synthesis, and ultimately benefit patients.

KEY RESPONSIBILITIES

• Set the strategy, roadmap, priorities, and measures of value for scientific evidence data capabilities, focused on Neuroscience.
• Build and deploy scalable AI-enabled workflows (e.g., AI agents) for evidence identification, extraction, curation, and analysis.
• Own delivery, investment decisions, and outcomes for AI-based scientific evidence extraction.
• Work with the data teams to establish fit-for-purpose data models and databases, provenance, quality controls, and reusable evidence assets.
• Define validation, evaluation, human-review, and responsible AI practices.
• Develop scientifically rigorous analysis workflows and quantify limitations (e.g., uncertainty).
• Partner with clinical, statistical, regulatory, scientific, legal, and technology stakeholders.
• Shape shared platform capabilities and ensure alignment with architecture, governance, and data-use requirements.
• Guide multidisciplinary delivery, maintain strong engineering practices, and mentor cross-functional contributors.
• Communicate priorities, tradeoffs, risks, progress, and impact to senior stakeholders.

QUALIFICATIONS

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