Principal Scientist, Data Science - DDSAI - Therapeutics Development Supply

Location: Spring House

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. Learn

more at  

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.

** Job Function:*
* Data Analytics & Computational Sciences

** Job Sub*
* ** Function:*
* Data Science

** Job Category:*
* Scientific/Technology

** All Job Posting Locations:*
* Cambridge, Massachusetts, United States of America, Spring House, Pennsylvania, United States of America

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* Job Description:

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* Johnson & Johnson Innovative Medicine is recruiting for  
** Principle Data Scientist - DDSAI - Therapeutics Development Supply*
* The primary location is flexible to Spring House, PA, Cambridge; MA; or Madrid or Barcelona, Spain.

** For candidates interested in Spain, please apply to requisition: R-081606*
* J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, immunology, neuroscience, cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market - from patients to practitioners and from clinics to hospitals.

To learn more about Johnson & Johnson Innovative Medicine visit

** POSITION SUMMARY*
* The R&D Data, Data Science and Artificial Intelligence (DDSAI) organization is seeking a hands-on  
** Principal Scientist, Data Science
** to design, build, and scale AI/ML, simulation, forecasting, optimization, decision intelligence and digital twin capabilities that support decision-making across Drug Product Development & Supply (DPDS), with primary focus on Therapeutics Development & Supply (TDS).

This individual contributor role will partner with development, technical operations, clinical supply chain, finance, and digital/data science stakeholders to translate complex scientific, operational, and planning processes into practical decision intelligence capabilities for TDS. The ideal candidate combines deep expertise in data science, operations research, scientific computing, and software development discipline with a track record of delivering measurable business impact in complex technical environments.

** KEY RESPONSIBILITIES*
* ** Digital Twin Development & Decision Intelligence*
* · Design, build, validate, and maintain digital twins and decision models of TDS/DPDS operations to support portfolio planning, capacity and resource allocation, demand/supply planning, scenario analysis, and operational decision-making.

· Apply data science, operations research, forecasting, simulation, uncertainty quantification, mathematical optimization, heuristics, and machine learning methods to solve high-value business and scientific planning problems.

· Translate complex development, manufacturing, clinical supply, and planning processes into fit-for-purpose computational models that capture uncertainty, constraints, and cross-functional interdependencies.

** Technical Delivery & Software Development Discipline*
* + Develop robust, reusable analytical workflows and modeling assets using Python and modern data science tooling, including cloud-based services.

+ Apply software engineering best practices, including version control, modular code design, testing, documentation, reproducibility, and code review.

+ Use modern development environments, including AI-assisted coding tools where appropriate, to accelerate delivery while maintaining quality, transparency, and…