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

Johnson & Johnson•Spring House, PA

About The Position

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 development and adoption of Operations Research and Decision Intelligence solutions across TDS. This senior individual technical contributor role combines hands-on modeling, technical leadership, and cross-functional influence. The role works with senior stakeholders, including Director- and VP-level leaders, to align priorities, clarify decision needs, and communicate recommendations, trade-offs, and risks. It develops reusable forecasting, optimization, simulation, and decision-modeling capabilities for portfolio and resource planning, business operations, laboratory and process digital twins, and clinical supply. The successful candidate has a strong background in Operations Research or Engineering and experience in pharmaceutical CMC development or supply chain.

Requirements

Ph.D. in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, Engineering, or a related quantitative discipline with 8 or more years of relevant experience; or a master’s degree with 10 or more 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.
Strong hands-on Python skills and demonstrated use of modern software-development and model-validation practices.
Track record of delivering quantitative decision-support solutions that achieve sustained adoption, with methods or components reused beyond an initial use case.
Demonstrated technical leadership through solution architecture, methodological improvement, standards, or mentorship.
Ability to formulate problems with subject matter experts, influence technical and business stakeholders, and communicate assumptions, trade-offs, and limitations clearly.

Nice To Haves

Experience in pharmaceutical R&D, CMC development, laboratory operations, clinical supply, manufacturing, or another regulated environment.
Experience with portfolio and resource forecasting, capacity planning, business operations analytics, or laboratory and process digital twins.
Experience integrating decision models with enterprise data products, planning systems, or production platforms.
Exposure to stochastic programming, Bayesian decision methods, agent-based modeling, reinforcement learning, or integration of AI/ML with optimization and simulation.
Publications, patents, open-source contributions, conference presentations, or comparable contributions in operations research or decision science.

Responsibilities

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, and 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.
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.
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, and 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.

Benefits

Eligibility to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
Eligibility to participate in the Company’s long-term incentive program.
Vacation: 120 hours per calendar year.
Sick time: 40 hours per calendar year, with different stated allowances for employees residing in Colorado or Washington.
Holiday pay, including Floating Holidays: 13 days per calendar year.
Work, Personal and Family Time: up to 40 hours per calendar year.
Parental Leave: 480 hours within one year of the birth, adoption, or foster care of a child.
Bereavement Leave: up to 240 hours for an immediate family member and 40 hours for an extended family member per calendar year.
Caregiver Leave: 80 hours in a 52-week rolling period.
Volunteer Leave: 32 hours per calendar year.
Military Spouse Time-Off: 80 hours per calendar year.