Associate Director, R&d Data, Data Science and AI - Data Strategy and Products

Johnson & Johnson · Pharma · Titusville, NJ +1

Associate Director role focused on defining and executing a data strategy for AI and knowledge graphs in R&D, specifically for biomedical data. The role involves leading the design, development, and stewardship of semantically rich biomedical data models and knowledge graphs, partnering with data engineering and AI teams to enable discovery and insights generation. The goal is to accelerate research and evidence generation by making data AI-ready and operationalizing capabilities across the product lifecycle.

What you'd actually do

  1. Define a multi‑year vision and roadmap for enterprise knowledge management through knowledge graphs, aligned with R&D priorities and therapeutic area strategies.
  2. Lead the design, development, and stewardship of semantically rich biomedical data models that unify heterogeneous omics, clinical trial, and experimental data into AI‑ready knowledge graphs firmly grounded in biochemistry.
  3. Partner with data engineering and platform teams to build, scale, and operate high‑performance knowledge graph services, enabling advanced querying, retrieval, and downstream analytics across therapeutic areas.
  4. Partner with advanced analytics and artificial intelligence teams to enable knowledge‑graph‑aware discovery, and insights generation across R&D use cases.
  5. Communicate knowledge graph strategy, maturity, and impact to senior leadership, supporting data‑driven R&D and portfolio decisions.

Skills

Required

  • Ph.D. in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields, emphasis on biomedical applications.
  • 8+ years of experience in pharma/biomedical R&D or commercial functions, with significant exposure to diverse biomedical data assets management, procurement, and/or strategy; or 6+ years of experience with an advanced degree.
  • Demonstrated scientific excellence in biomedical R&D through consistent publishing as a lead author in the domains of bioinformatics, knowledge graphs and data science.
  • Deep experience with data quality control in high-stakes pharmaceutical or clinical domains, and regulatory requirements around healthcare data.
  • Prior experience and proven track record with leading multidisciplinary teams and influencing cross-functional stakeholders without direct authority.

What the JD emphasized

  • Deep experience with data quality control in high-stakes pharmaceutical or clinical domains, and regulatory requirements around healthcare data.
  • Demonstrated scientific excellence in biomedical R&D through consistent publishing as a lead author in the domains of bioinformatics, knowledge graphs and data science.

Other signals

  • knowledge graphs
  • biomedical data products
  • AI-ready knowledge graphs
  • knowledge-graph-aware discovery