Manager Simulation Modeler Engineer

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 Med Tech, 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.

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As guided by Our Credo, Johnson & Johnson is responsible to its 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.

Supply Chain Engineering

Process Engineering

People Leader

Raritan, New Jersey, United States of America

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

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We are searching for the best talent for a Manager Simulation Modeler Engineer to join our Team. This is an onsite/hybrid position located in Raritan, NJ.

Are you interested in joining a team that is positively impacting patients' lives by ensuring high quality in our cell therapy products? Apply today for this exciting opportunity to be part of the CAR-T team!

There is a pre-identified candidate for this position, but all candidates will be considered.

Manager Simulation Modeler Engineer: A leadership-focused engineering role dedicated to building and delivering high-impact discrete-event simulations using Simio. Optimization is secondary; the primary mission is to drive process understanding, improvement, and adoption through rigorous simulation study, robust change management, and cross-functional collaboration. Knowledge of pharmaceutical manufacturing processes is preferred. The Manager will work in a matrix environment, both within Johnson & Johnson and with our CAR-T collaboration partner, Legend Biotech.

• Lead the design, development, and delivery of end-to-end discrete-event simulation models in Simio to analyze and optimize complex manufacturing and operations processes.
• Drive process improvement programs using simulation to identify bottlenecks, quantify benefits, and define implementation roadmaps.
• Guide change management activities to ensure successful adoption of simulation insights, including stakeholder engagement, training, and communication plans.

• Architect, build, validate, and maintain discrete-event models in Simio to represent current and future-state production and logistics processes.
• Lead process improvement projects from scoping through execution, capturing clear value propositions (capacity, throughput, cycle times, quality, cost) and driving realization plans.
• Develop and maintain modeling standards, templates, and documentation to enable repeatable, scalable simulation work across teams.
• Lead change initiatives associated with simulation-driven improvements, including stakeholder communication plans, training material, and adoption tracking.
• Facilitate decision-making forums by delivering clear, data-driven narratives and visuals; produce executive-friendly reports and dashboards.

• Minimum 5 years of hands-on experience in discrete-event simulation, preferably with Simio; a track record of delivering impact through simulation in complex environments.
• Strong capability in modeling, data analysis, and storytelling with data; able to translate complex models into clear, actionable business recommendations.
• Proficiency with programming/scripting to support models and data processing (e.g., Python, R, or equivalent) and familiarity with data visualization tools.
• Excellent communication, presentation, and leadership skills; proven ability to lead multi-functional teams and drive organizational change.
• Bachelor's degree in Engineering, Operations Research, Industrial Engineering, Chemical Engineering, Computer Science, Statistics, or a related discipline. Master's degree preferred.

• Experience with pharmaceutical manufacturing processes and GMP/quality systems is highly desirable.
• Exposure to optimization concepts (e.g., LP, MILP, MINLP) and their integration with simulation; while optimization is a secondary focus, familiarity is advantageous.
• Experience implementing simulation-driven solutions across manufacturing floors or large-scale operations.
• Knowledge of process improvement methodologies (e.g., Lean, Six Sigma) and their application via…