Senior Scientist, Modeler

Johnson & Johnson Innovative Medicine•Malvern, PA

1d•Hybrid

About The Position

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. About Innovative Medicine 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. Learn more at https://www.jnj.com/innovative-medicine We are searching for the best talent for Senior Scientist, Modeler, to join our team in Malvern or Spring House, PA. Purpose: In this role, you will serve as an individual contributor with expertise in applied modeling for Cell and Gene Therapy process and product development. The role will build fit-for-purpose models to support a broad range of data consumption use cases, including time series modeling, process characterization, optimization, scale translation, data interpretation, and decision-making across development teams. In addition, this role will require innate familiarity with the foundational requirement needed to support end-to-end Digital Twins by scalable modeling components that connect process/analytical knowledge, experimental data, mechanistic and statistical models, and user-facing tools. The successful candidate will collaborate closely with scientists, engineers, data and automation partners, Digital Twin leads, and project teams to identify high-value modeling use cases, translate scientific questions into model-based workflows, and deliver interpretable outputs that support Cell and Gene Therapy development strategies.

Requirements

A minimum of a BS degree in a core science or engineering field, including biology, chemistry, chemical/biochemical engineering, biomedical engineering, physics, bioinformatics, data science, applied mathematics, or a related discipline, with at least 4 years of relevant experience; OR an MS or equivalent with at least 2 years of relevant experience; OR a PhD or equivalent with 0-1 year of relevant experience is required.
Experience developing and applying time series, mechanistic, statistical, hybrid, machine learning, or multivariate models to complex scientific or engineering data is required.
Ability to translate scientific questions into modeling strategies, define appropriate assumptions, communicate model limitations, and interpret model outputs for non-modeling audiences is required.
Advanced skills with one or more programming languages or modeling environments are required. Examples may include Python, R, MATLAB, Julia, C++, Java, .NET, or equivalent tools.
Proficiency with statistics, algorithm design, data analysis, model quality attributes, and model verification/validation concepts is required.
Strong collaboration and communication skills, including the ability to work across global, cross-functional scientific, engineering, data, automation, and IT teams, are required.

Nice To Haves

Experience with pharmaceutical development, biologics development, Cell and Gene Therapy process development, or GxP-adjacent development environments is preferred.
Experience contributing to reusable modeling frameworks, simulation workflows, digital twin initiatives, decision-support applications, or user-facing modeling tools is preferred.
Experience with process analytical technologies, in-line/at-line/off-line data streams, chemometrics, Raman spectroscopy, bioreactor data, chromatography data, or other process development data sources is preferred.
Experience with cloud, software development, or collaboration tools is preferred. Examples may include Azure, AWS, Git, JIRA, Confluence, agile/scrum practices, application development, or full-stack development.

Responsibilities

Build and deploy fit-for-purpose models that support routine Cell and Gene Therapy development activities, including time series modeling, process characterization, optimization, scale-up/scale-down translation, comparability assessments, and data-driven troubleshooting.
Develop mechanistic, statistical, hybrid, and/or machine learning models that translate complex development data into actionable insights for scientists, engineers, and project teams.
Create user-accessible modeling solutions, dashboards, workflows, or decision-support tools that enable project teams to apply model outputs in day-to-day development decisions.
Partner with scientists, engineers, data scientists, automation experts, IT architects, and Digital Twin leads to define data requirements, model inputs, and reusable data structures needed to support modeling workflows and broader data science initiatives.
Contribute modeling components that support development of end-to-end Cell and Gene Therapy Digital Twins, including unit operation models, model-ready data structures, simulation workflows, and integration-ready outputs.
Support model verification, validation, documentation, lifecycle management, and appropriate governance to ensure models are reliable, interpretable, and fit for their intended use.
Define and lead departmental strategy for model implementation, including embedding modeling tools into scientific workflows and managing the associated change management activities.
Advance a modeling culture within Cell and Gene Therapy development by identifying high-impact use cases, coaching scientific teams on model interpretation, and promoting data-driven decision-making.