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# Director, Data Science - GenAI - Neuroscience

- **Company:** Johnson & Johnson
- **Location:** Cambridge, MA, United States
- **Experience:** Expert
- **Salary:** $164,000.0 - $282,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Health Informatics, Computational Biology, Computer Literacy, Data Visualization, Python (Programming Language), Software Engineering, Large Language Models, Generative AI, Build Management, Information Technology, Human in the Loop
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/director-data-science-genai-neuroscience-cambridge-ma--59358464-5bcd-4ce1-b2d0-da1cce2cfdde

## About the Role

Data Science, Neuroscience, Medicine, Healthcare, Disease Prevention and Control, Diversity, Data Analysis, Data Science, Neuroscience, Artificial Intelligence (AI), * PhD in computer science, computational biology, genetics, genomics, medical informatics, or a related quantitative field; or MS with additional relevant experience.

 * 8+ years of experience in pharmaceutical, biotech, or healthcare analytics, with experience setting technical direction.
 * Within the last 18 months, you should have hands-on experience building agentic systems and deploying AI, NLP, or generative AI solutions, leveraging LLMs, retrieval, grounding, and evaluation.
 * Strong ability to critically assess scientific evidence, with optional expertise in neuroscience.
 * Strong Python skills and sound software engineering practices.
 * Experience leading multidisciplinary technical delivery and influencing across organizational boundaries.
 * Demonstrated ability to define priorities, make evidence-based tradeoffs, and deliver measurable value.
 * Strong communication skills with technical, scientific, and senior non-technical stakeholders.
 * Experience developing within shared platforms, architecture standards, and governance frameworks.
 * Experience with genetics, multi-omics, imaging, ontologies, or scientific knowledge systems preferred.
 * Exposure to regulated environments, AI governance, and human-in-the-loop systems is preferred.
 * Optional: industry experience in drug discovery, clinical development, neuroscience.

This position will be located at one of our US sites (Raritan, NJ; Titusville, NJ; Cambridge, MA; Spring House, PA; San Diego, CA). Travel may be required as needed., Preferred Skills:

Advanced Analytics, Budget Management, Compliance Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Program Management, Strategic Thinking, Succession Planning

## Description

The Director will lead the design, development, and deployment of AI, generative AI, and agentic AI workflow solutions for Neuroscience R&D, working across datatypes, including clinical, omics and other molecular data, and medical imaging data. Working closely with scientists and data teams, the candidate will translate priority research needs into scalable tools and capabilities (e.g., AI co-scientists) that improve how scientific information is discovered, integrated, and used by scientists, in a way that stays current with evolving scientific advances.

This hands-on leader will set technical direction, guide multidisciplinary delivery, establish evaluation and responsible AI practices, and build the reusable solutions within the enterprise platforms, in partnership with cross-functional teams in DDSAI and the Neuroscience TA (therapeutic area). The role is accountable for the platform build and evolution, scientific rigor and evaluation, user adoption, and measurable value from the Neuroscience AI portfolio., * Set the Neuroscience AI strategy, portfolio, roadmap, and measures of value.

 * Build and deploy scalable agentic AI and generative AI solutions for priority scientific needs.
 * Own delivery, investment decisions, and outcomes for the Neuroscience AI portfolio.
 * Ensure scientific rigor, appropriate evidence use, and reliable domain representation.
 * Establish evaluation standards, expert validation, and responsible AI practices.
 * Shape shared platform capabilities and develop reusable solutions aligned with enterprise architecture.
 * Guide multidisciplinary teams and maintain strong engineering and lifecycle practices.
 * Partner with scientists and leaders to prioritize needs, validate solutions, and drive adoption.
 * Communicate technical choices, risks, progress, and impact to senior stakeholders.