Principal Scientist, Operations Research & Decision Science- R&D DDSAI - Therapeutics Development & Supply (TDS)

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 jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: Scientific/Technology All Job Posting Locations: Madrid, Spain, Spring House, Pennsylvania, United States of America Job Description: Johnson & Johnson Innovative Medicine is recruiting for Principal Scientist, Operations Research & Decision Science- R&D DDSAI - Therapeutics Development & Supply (TDS) The primary location for this position is open to Spring House, PA or Madrid, Spain J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, immunology, neuroscience, cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market - from patients to practitioners and from clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine visit https://innovativemedicine.jnj.com/ POSITION SUMMARY The R&D Data, Data Science and Artificial Intelligence (DDSAI) organization is seeking a hands-on Principal Scientist, Operations Research & Decision Science to design, build, and scale simulation, optimization, digital twin, and decision-support capabilities across Therapeutics Development & Supply (TDS), including Chemistry, Manufacturing & Controls (CMC) and Clinical Supply Chain (CSC). This individual contributor will translate complex development, manufacturing, portfolio, capacity, resource, and clinical supply processes into rigorous computational models. The ideal candidate combines deep expertise in operations research, industrial engineering, mathematical modeling, and scientific computing with the software engineering discipline required to deploy trusted solutions in enterprise decision workflows. KEY RESPONSIBILITIES Operations Research & Mathematical Optimization Formulate and solve optimization problems involving portfolio prioritization, resource allocation, capacity planning, and resource scheduling. Apply linear and mixed-integer programming, nonlinear optimization, stochastic programming, decomposition, heuristics, and multi-objective methods as appropriate to the decision context. Develop models that make constraints, uncertainty, risk, and tradeoffs explicit and convert model outputs into clear decision recommendations. Simulation, Digital Twins & Systems Modeling Design, build, validate, and maintain digital twins of TDS and CSC operations to evaluate future scenarios, policies, investments, and operating strategies. Develop discrete-event, Monte Carlo, agent-based, system dynamics, and hybrid simulations when appropriate to represent complex operational systems. Establish fit-for-purpose practices for model verification, validation, calibration, sensitivity analysis, uncertainty quantification, and ongoing performance monitoring. Create reusable modeling components and platforms that can be extended across products, programs, sites, and business processes. Technical Delivery & Scaled Capability Development Develop robust, reusable modeling workflows and decision-support products using Python and modern scientific computing, optimization, simulation, and cloud-based tooling. Apply software engineering best practices, including modular design, version control, testing, documentation, reproducibility, code review, and maintainable interfaces. Partner with data engineering, product, architecture, and platform teams to integrate models with enterprise data and embed outputs into recurring planning and operational workflows. Cross-Functional Leadership & Business Impact Partner with leaders and subject-matter experts across TDS, CSC, technical operations, portfolio management, finance, and digital organizations to define decisions, requirements, constraints, and measures of value. Lead technical work across multiple initiatives while remaining a hands-on modeler and developer. Communicate model assumptions, limitations, results, and recommendations clearly to technical and non-technical audiences. Mentor colleagues and provide technical direction to internal teams, consultants, and external collaborators. QUALIFICATIONS Required Advanced degree in Operations Research, Industrial Engineering, Systems Engineering, Applied Mathematics, Management Science, Computer Science, Chemical Engineering, or a related quantitative field. 5+ years of relevant experience applying optimization, simulation, stochastic modeling, decision analysis, or related operations research methods to complex operational problems. Demonstrated depth in at least two of the following: mathematical programming, discrete-event simulation, stochastic optimization, scheduling, network optimization, resource allocation, inventory optimization, or decision-making under uncertainty. Strong Python programming skills and practical experience with optimization or simulation frameworks such as Pyomo, Gurobi, CPLEX, OR-Tools, SimPy, AnyLogic, Simio, Arena, or equivalent tools. Proven record of delivering computational models or decision-support products that influenced consequential business or operational decisions. Ability to provide technical leadership in cross-functional environments while remaining a hands-on individual contributor. Preferred Ph.D. in Operations Research, Industrial Engineering, Systems Engineering, Applied Mathematics, Management Science, or a closely related discipline. Experience in pharmaceutical development, CMC, manufacturing, clinical supply, supply chain, portfolio planning, capacity planning, resource planning, or another complex operational environment. Experience deploying simulation, optimization, or digital twin solutions into enterprise workflows and maintaining them as durable products. Experience integrating forecasting, machine learn