Sr Director, Head of Data Science & Digital Health – Therapeutics Development &
Scorpion Therapeutics, Malverne Park Oaks, New York, United States
Role Summary
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. Partner with TDS teams and the broader DPDS organization to 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. Lead digital twins, predictive modeling, and GenAI-powered knowledge acceleration to industrialize development processes and strengthen J&J’s leadership in innovative medicine through collaboration with TDS functions, JJT, and enterprise data/AI partners. 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 tools, standards, and scalable capabilities; support citizen data scientists and DOS teams within TDS; ensure model governance and interoperability; create pathways to scale models; collaborate across TDS modalities, DPDS, and R&D. 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 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 analytics for discovery, development and manufacturing. 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. Qualifications
Required: PhD (or equivalent experience) in Chemical/Biochemical Engineering, Bioinformatics Pharmaceutical Sciences, AI/ML, Applied Math/Statistics or related field. Required: 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. Required: Demonstrated outcomes in process and analytical development or clinical supply analytics. Required: Fluency with modern ML techniques, and MLOps on cloud platforms; experience integrating with LIMS/ELN/MES. Required: Proven ability to synchronize tech and data science roadmaps, and drive portfolio value realization. Required: Excellent communication and matrix leadership across scientific, technical, and business stakeholders in a global organization. Preferred: Experience across multi-modality portfolios (small/large molecules, cell & gene). Preferred: Familiarity with GenAI/LLMs in R&D settings, agents, and AI deployments in a regulatory setting. Preferred: Prior collaboration with External Innovation partners in development/manufacturing technologies. Skills
Advanced Analytics Budget Management Business Alignment Compliance Management Consulting Critical Thinking Data Analysis Data Privacy Standards Data Quality Data Reporting Data Savvy Data Science Data Visualization Developing Others Digital Fluency Inclusive Leadership Leadership Strategic Thinking Additional Requirements
Travel: Up to ~25% domestic/international
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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. Partner with TDS teams and the broader DPDS organization to 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. Lead digital twins, predictive modeling, and GenAI-powered knowledge acceleration to industrialize development processes and strengthen J&J’s leadership in innovative medicine through collaboration with TDS functions, JJT, and enterprise data/AI partners. 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 tools, standards, and scalable capabilities; support citizen data scientists and DOS teams within TDS; ensure model governance and interoperability; create pathways to scale models; collaborate across TDS modalities, DPDS, and R&D. 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 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 analytics for discovery, development and manufacturing. 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. Qualifications
Required: PhD (or equivalent experience) in Chemical/Biochemical Engineering, Bioinformatics Pharmaceutical Sciences, AI/ML, Applied Math/Statistics or related field. Required: 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. Required: Demonstrated outcomes in process and analytical development or clinical supply analytics. Required: Fluency with modern ML techniques, and MLOps on cloud platforms; experience integrating with LIMS/ELN/MES. Required: Proven ability to synchronize tech and data science roadmaps, and drive portfolio value realization. Required: Excellent communication and matrix leadership across scientific, technical, and business stakeholders in a global organization. Preferred: Experience across multi-modality portfolios (small/large molecules, cell & gene). Preferred: Familiarity with GenAI/LLMs in R&D settings, agents, and AI deployments in a regulatory setting. Preferred: Prior collaboration with External Innovation partners in development/manufacturing technologies. Skills
Advanced Analytics Budget Management Business Alignment Compliance Management Consulting Critical Thinking Data Analysis Data Privacy Standards Data Quality Data Reporting Data Savvy Data Science Data Visualization Developing Others Digital Fluency Inclusive Leadership Leadership Strategic Thinking Additional Requirements
Travel: Up to ~25% domestic/international
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