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
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 learning, or AI methods with prescriptive models and decision-support systems.
Why This Role Is Unique
This is a rare opportunity to grow in one of the world's most ambitious and fast-growing R&D Data Science organizations, shaping how advanced modeling, simulation, and optimization transform decision-making across Drug Product Development & Supply, with direct impact on Therapeutics Development & Supply. Your work will directly improve how Johnson & Johnson plans and executes its development portfolio, allocates critical resources, and accelerates delivery of next-generation therapies to patients globally.
Required Skills:
Preferred Skills:
Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis
The anticipated base pay range for this position is :
$117,000.00 - $201,250.00
Additional Description for Pay Transparency:
Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
This position is eligible to participate in the Company’s long-term incentive program.
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of 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 period10 days
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits
