Senior Principal Scientist, Data Science - R&D DDSAI - Therapeutics Development & Supply (TDS)

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Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Malvern, Pennsylvania, United States of America, Spring House, Pennsylvania, United States of America

Job Description:

Position Summary

Therapeutics Development & Supply (TDS) bridges scientific discovery and clinical application across Chemistry, Manufacturing and Controls (CMC), device development, and clinical supply chain.

The R&D Data, Data Science & AI (DDSAI) organization is seeking a Senior Principal Scientist, Data Science to lead the development and adoption of Operations Research and Decision Intelligence solutions across TDS. This is a senior individual technical contributor role combining hands-on modeling, technical leadership, and cross-functional influence. This role will work with senior stakeholders, Director- and VP-level, across TDS, aligning priorities, clarifying decision needs, and communicating recommendations, trade-offs, and risks.

The role will develop reusable forecasting, optimization, simulation, and decision-modeling capabilities for portfolio and resource planning, business operations, laboratory and process digital twins, and clinical supply. A successful candidate has a strong background in Operations Research or Engineering and has experience in pharmaceutical CMC development or supply chain.

Key Responsibilities

Model Development & Decision Support

• Design, build, validate, and deliver forecasting, optimization, simulation, and decision-support solutions for complex scientific, planning, and operational problems.
• Develop long- and short-term portfolio, workload, resource, and capacity forecasts; quantify uncertainty, dependencies, and scenario sensitivities.
• Develop business operations analytics and laboratory or process digital twins that connect demand, workflow, equipment, capacity, and performance to actionable decisions.
• Apply operations research methods to clinical supply and development planning, making assumptions, trade-offs, and model limitations explicit.

Technical Leadership & Sustainable Delivery

• Develop reusable modeling frameworks, reference implementations, and practical guidance for forecasting, mathematical optimization, simulation, decision analysis, and uncertainty quantification.
• Apply disciplined software and model-development practices, including modular code, version control, testing, documentation, reproducibility, peer review, sensitivity analysis, and monitoring.
• Partner with J&J Technology and DDSAI teams on data integration, deployment, observability, security, support, and lifecycle ownership; work with quality and compliance partners where regulated controls are required.
• Provide technical guidance and mentorship to data scientists and quantitative practitioners through problem formulation, model architecture, code review, and validation.

Collaboration & Adoption

• Work with TDS scientists, engineers, laboratory leaders, Clinical Supply Chain, business operations, Digital Operations & Strategy, and Finance to define decision needs and embed solutions into established workflows.
• Collaborate with DDSAI data product, ontology, AI/ML, and platform teams on shared definitions, reusable data products, methods, and components.
• Communicate recommendations, assumptions, uncertainty, and limitations clearly to technical and business stakeholders, including senior leaders; build adoption through evidence and effective decision framing.
• Contribute to the Operations Research and Decision Intelligence roadmap, technical forums, communities of practice, and evaluation of emerging methods or external solutions.

Qualifications

Required

• Ph.D. in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, Engineering, or a related quantitative discipline with 8+ years of relevant experience; or a master’s degree with 10+ years of relevant experience.
• Advanced expertise in mathematical optimization, including linear and mixed-integer programming; simulation, including Monte Carlo or discrete-event methods; and forecasting and uncertainty analysis.

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