Principal Scientist, Operations Research – Decision Science

Johnson & Johnson

. Design, build, and scale simulation, optimization, digital twin, and decision-support capabilities across Therapeutics Development & Supply, including CMC and Clinical Supply Chain .

Posted 9/21/2026full-timeSpring House • Pennsylvania • United StatesLead💰 $117,000 - $201,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in optimization, simulation, and decision-support modeling within complex operational environments, utilizing advanced programming skills in Python and experience with industry-standard frameworks. Capable of leading cross-functional teams while delivering impactful computational models that drive strategic business decisions.

Highest-signal resume keywords

OptimizationSimulationPython ProgrammingMathematical ProgrammingDecision Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

OptimizationSimulationStochastic ModelingMathematical ProgrammingResource AllocationInventory OptimizationDecision-Making Under UncertaintyDiscrete-Event SimulationNetwork OptimizationCapacity Planning

Soft Skills

Technical LeadershipCommunicationMentoring

Tools & Technologies

PyomoGurobiCPLEXOR-ToolsSimPyAnyLogicSimioArena

Industry Keywords

Pharmaceutical DevelopmentClinical SupplySupply ChainPortfolio PlanningComplex Operational Environment

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

Design, build, and scale simulation, optimization, digital twin, and decision-support capabilities across Therapeutics Development & Supply, including CMC and Clinical Supply Chain
Translate development, manufacturing, portfolio, capacity, resource, and clinical supply processes into rigorous computational models
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
Develop models that make constraints, uncertainty, risk, and tradeoffs explicit and convert outputs into decision recommendations
Design, build, validate, and maintain digital twins of TDS and CSC operations
Develop discrete-event, Monte Carlo, agent-based, system dynamics, and hybrid simulations
Establish practices for model verification, validation, calibration, sensitivity analysis, uncertainty quantification, and performance monitoring
Create reusable modeling components and platforms across products, programs, sites, and business processes
Develop robust, reusable modeling workflows and decision-support products using Python, 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 workflows
Partner with leaders and subject-matter experts across TDS, CSC, technical operations, portfolio management, finance, and digital organizations
Lead technical work across multiple initiatives as a hands-on modeler and developer
Communicate assumptions, limitations, results, and recommendations to technical and non-technical audiences
Mentor colleagues and provide technical direction to internal teams, consultants, and external collaborators

Requirements

What you’ll need

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: mathematical programming, discrete-event simulation, stochastic optimization, scheduling, network optimization, resource allocation, inventory optimization, or decision-making under uncertainty
Strong Python programming skills
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 a related discipline
Preferred: Experience in pharmaceutical development, CMC, manufacturing, clinical supply, supply chain, portfolio planning, capacity planning, resource planning, or another complex operational environment
Preferred: Experience deploying simulation, optimization, or digital twin solutions into enterprise workflows and maintaining them as durable products
Preferred: Experience integrating forecasting, machine learning, or AI methods with prescriptive models and decision-support systems

Benefits

Comp & perks

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; employees residing in Colorado – 48 hours per calendar year; employees residing in Washington – 56 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