About The Position

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 https://www.jnj.com/innovative-medicine Role Summary Therapeutics Development & Supply (TDS) is the bridge between scientific discovery and clinical application, encompassing Chemistry, Manufacturing & Controls (CMC), Device Development, and Clinical Supply Chain. This organization ensures that every molecule, modality, and delivery system is robustly developed, scaled, and supplied under rigorous quality and regulatory standards. We are seeking a Global Head of Data Science & Digital Health – TDS to enable and embed AI/ML and advanced analytics into the core of drug development and supply. In close partnership with TDS teams and the broader DPDS organization, this leader will transform process design, scale-up, and clinical supply optimization into data-driven engines of speed, reliability, and compliance across all modalities—small molecules, biologics, and cell & gene therapies. By championing digital twins, predictive modeling, and GenAI-powered knowledge acceleration, this role will industrialize development processes and strengthen J&J’s leadership in innovative medicine through deep collaboration with TDS functions, JJT, and enterprise data/AI partners.

Requirements

  • PhD (or equivalent experience) in Chemical/Biochemical Engineering, Bioinformatics Pharmaceutical Sciences, AI/ML, Applied Math/Statistics or related field.
  • 15+ years applied data science/AI leadership in biopharma development/CMC and/or clinical supply, including experience leading multi-disciplinary teams in a matrix setting.
  • Demonstrated outcomes in process and analytical development or clinical supply analytics.
  • Fluency with modern ML techniques, and MLOps on cloud platforms; experience integrating with LIMS/ELN/MES.
  • Proven ability to synchronize tech and data science roadmaps, and drive portfolio value realization.
  • Excellent communication and matrix leadership across scientific, technical, and business stakeholders in a global organization.

Nice To Haves

  • Experience across multi-modality portfolios (small/large molecules, cell & gene).
  • Familiarity with GenAI/LLMs in R&D settings, agents, and AI deployments in a regulatory setting.
  • Prior collaboration with External Innovation partners in development/manufacturing technologies.

Responsibilities

  • Strategy & Portfolio Leadership: Partner to define and execute the TDS Data Science strategy aligned to TDS/DPDS priorities; build a multi-year roadmap for data, analytics, AI/ML (incl. GenAI); manage portfolio prioritization, funding, and value realization.
  • CMC, Product & Process Development: Enable scientists and engineers to build and expand scientific models by providing an ecosystem of tools, standards, and scalable capabilities. Support citizen data scientists and DOS teams within TDS through training and frameworks, ensure model governance and interoperability, and create pathways to scale models for broader utilization and reuse. Provide expert guidance and advanced data/modeling support where needed, while fostering collaboration across TDS modalities, DPDS, and the broader R&D organization.
  • Device/Combination Product & Platform Engineering: Apply reliability modeling, image/signal analytics, and simulation to device/combination product performance and manufacturability.
  • Clinical Supply Chain Analytics: Build forecasting, simulation and optimization engines for clinical supply, IRT signal integration, and risk-based inventory strategies; develop scenario planning/digital twin for clinical supply networks.
  • Platforms, Data & MLOps: Co-own with DOS and JJT the data and ML platform architecture, MLOps, model monitoring, and governance for GxP contexts.
  • GenAI & Knowledge Acceleration: Lead targeted use of GenAI/LLMs for technical documentation, regulatory authoring aids, and knowledge acceleration.
  • External Innovation & Partnerships: Scout and partner with academia/startups/CROs on cutting-edge discovery, development and manufacturing analytics.
  • People & Community Leadership: Build and lead a global team of data scientists, AI/ML engineers and applied statisticians; upskill TDS Scientists and Engineers with Data and AI/ML fluency.
  • Quality, Safety & Compliance: Ensure data integrity, model validation, computerized systems compliance, and transparent model interpretability in regulated environments.

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What This Job Offers

Job Type

Full-time

Career Level

Director

Education Level

Ph.D. or professional degree

Number of Employees

5,001-10,000 employees

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