Principal Scientist, Operations Research & Decision Science- R&D DDSAI - Therapeutics Development & Supply (TDS)
Johnson & Johnson Innovative Medicine
•$117,000 - $201,250•Hybrid
About The Position
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.
Requirements
- 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.
Nice To Haves
- 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 learning, or AI methods with prescriptive models and decision-support systems.
Responsibilities
- 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.
- 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.
- 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.
- 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.
Benefits
- Consolidated retirement plan (pension)
- Savings plan (401(k))
- Long-term incentive program
- Vacation –120 hours per calendar year
- Sick time - 40 hours per calendar year
- 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/foster care of a child
- Bereavement Leave – 240 hours for an immediate family member: 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
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What This Job Offers
Job Type
Full-time
Career Level
Principal
