Sr Director, Head of Data Science & Digital Health – Preclinical Sciences & Translational Safety (psts)

Johnson & Johnson Johnson & Johnson · Pharma · Spring House, PA +1

Lead the data science strategy for Preclinical Sciences & Translational Safety (PSTS), focusing on advanced automation, data integration, FAIR data practices, and the use of ML/AI. Develop and implement scalable data pipelines, ML/AI models, and analytics to support translational safety and preclinical workflows. Champion data governance, MLOps, and Responsible AI. Lead a team of data scientists and engineers, and collaborate on emerging technologies like generative and agentic AI.

What you'd actually do

  1. Develop and execute a comprehensive data strategy for PSTS, focusing on advanced automation, data integration, and FAIR data practices, and the use of ML/AI in close alignment with PSTS and IT.
  2. Lead the design and implementation of scalable data pipelines, ML/AI models, and analytics to support translational safety and preclinical workflows.
  3. Champion data governance, analytics, model lifecycle management (MLOps), and Responsible AI standards into reusable capabilities that can be shared elsewhere in the organization.
  4. Lead a core team of data scientists and engineers to support PSTS in reaching its strategic goals.
  5. Collaborate with PSTS teams, IT, R&D Data Science, and external partners to jointly introduce emerging technologies such as generative and agentic AI, multimodal analytics, and advanced automation tools that benefit PSTS’s business objectives.

Skills

Required

  • PhD or equivalent experience in Computational Biology, Toxicology, Pharmacology, AI/ML, Applied Math/Statistics or related field.
  • 7+ years in data science for translational safety, drug discovery, or related domains, with experience leading teams in a matrix setting.
  • Proven expertise in creating high impact R&D innovations through data science, data engineering, and automation within scientific domains.
  • Strong experience leading the application/creation of ML/AI methods while demonstrating a deep understanding of translational safety and preclinical workflows.
  • Demonstrated success in delivering interoperable data products and scalable analytics platforms.
  • Excellent communication and matrix leadership across scientific, technical, and business stakeholders in a global organization.

Nice to have

  • strategic vision
  • collaborative influence
  • innovation mindset
  • talent development
  • communication excellence

What the JD emphasized

  • advanced automation
  • data integration
  • ML/AI
  • translational safety
  • preclinical workflows
  • data governance
  • model lifecycle management (MLOps)
  • Responsible AI
  • generative and agentic AI
  • multimodal analytics

Other signals

  • scale advanced analytics and AI capabilities
  • ML/AI models
  • generative and agentic AI
  • multimodal analytics