Senior Principal Scientist, Data Science - R&D DDSAI - Therapeutics Development & Supply (TDS)
Johnson & Johnson is hiring a Senior Principal Scientist, Data Science - R&D DDSAI - Therapeutics Development & Supply (TDS). It pays $137k-$236k a year and Level rates it ; you can apply on Johnson & Johnson.
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- Level rates this role Little AI ●○○○: aI is not part of the work.
- Level classifies it as a lead role.
- Level lists 1,800+ other open roles at Johnson & Johnson.
- The role was posted in the last few days.
AI in this role
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.
Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Data ScienceJob Category:
Scientific/TechnologyAll Job Posting Locations:
Malvern, Pennsylvania, United States of America, Spring House, Pennsylvania, United States of AmericaJob Description:
Position SummaryTherapeutics Development & Supply (TDS) bridges scientific discovery and clinical application across Chemistry, Manufacturing and Controls (CMC), device development, and clinical supply chain.
The R&D Data, Data Science & AI (DDSAI) organization is seeking a Senior Principal Scientist, Data Science to lead the development and adoption of Operations Research and Decision Intelligence solutions across TDS. This is a senior individual technical contributor role combining hands-on modeling, technical leadership, and cross-functional influence. This role will work with senior stakeholders, Director- and VP-level, across TDS, aligning priorities, clarifying decision needs, and communicating recommendations, trade-offs, and risks.
The role will develop reusable forecasting, optimization, simulation, and decision-modeling capabilities for portfolio and resource planning, business operations, laboratory and process digital twins, and clinical supply. A successful candidate has a strong background in Operations Research or Engineering and has experience in pharmaceutical CMC development or supply chain.
Key Responsibilities
Model Development & Decision Support
- Design, build, validate, and deliver forecasting, optimization, simulation, and decision-support solutions for complex scientific, planning, and operational problems.
- Develop long- and short-term portfolio, workload, resource, and capacity forecasts; quantify uncertainty, dependencies, and scenario sensitivities.
- Develop business operations analytics and laboratory or process digital twins that connect demand, workflow, equipment, capacity, and performance to actionable decisions.
- Apply operations research methods to clinical supply and development planning, making assumptions, trade-offs, and model limitations explicit.
Technical Leadership & Sustainable Delivery
- Develop reusable modeling frameworks, reference implementations, and practical guidance for forecasting, mathematical optimization, simulation, decision analysis, and uncertainty quantification.
- Apply disciplined software and model-development practices, including modular code, version control, testing, documentation, reproducibility, peer review, sensitivity analysis, and monitoring.
- Partner with J&J Technology and DDSAI teams on data integration, deployment, observability, security, support, and lifecycle ownership; work with quality and compliance partners where regulated controls are required.
- Provide technical guidance and mentorship to data scientists and quantitative practitioners through problem formulation, model architecture, code review, and validation.
Collaboration & Adoption
- Work with TDS scientists, engineers, laboratory leaders, Clinical Supply Chain, business operations, Digital Operations & Strategy, and Finance to define decision needs and embed solutions into established workflows.
- Collaborate with DDSAI data product, ontology, AI/ML, and platform teams on shared definitions, reusable data products, methods, and components.
- Communicate recommendations, assumptions, uncertainty, and limitations clearly to technical and business stakeholders, including senior leaders; build adoption through evidence and effective decision framing.
- Contribute to the Operations Research and Decision Intelligence roadmap, technical forums, communities of practice, and evaluation of emerging methods or external solutions.
Qualifications
Required
- Ph.D. in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, Engineering, or a related quantitative discipline with 8+ years of relevant experience; or a master’s degree with 10+ years of relevant experience.
- Advanced expertise in mathematical optimization, including linear and mixed-integer programming; simulation, including Monte Carlo or discrete-event methods; and forecasting and uncertainty analysis.
- Strong hands-on Python skills and demonstrated use of modern software-development and model-validation practices.
- Track record of delivering quantitative decision-support solutions that achieve sustained adoption, with methods or components reused beyond an initial use case.
- Demonstrated technical leadership through solution architecture, methodological improvement, standards, or mentorship. People-management experience is not required.
- Ability to formulate problems with subject matter experts, influence technical and business stakeholders, and communicate assumptions, trade-offs, and limitations clearly.
Preferred
- Experience in pharmaceutical R&D, CMC development, laboratory operations, clinical supply, manufacturing, or another regulated environment.
- Experience with portfolio and resource forecasting, capacity planning, business operations analytics, or laboratory and process digital twins.
- Experience integrating decision models with enterprise data products, planning systems, or production platforms.
- Exposure to stochastic programming, Bayesian decision methods, agent-based modeling, reinforcement learning, or integration of AI/ML with optimization and simulation.
- Publications, patents, open-source contributions, conference presentations, or comparable contributions in operations research or decision science.
Why This Role Is Unique
This role connects strategic portfolio planning with day-to-day scientific and operational decisions. You will combine hands-on modeling with technical leadership to deliver reusable capabilities across TDS, working at the intersection of science, strategy, data, and technology.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.
#JRDDS
#JNJDataScience
JNJIMRND-DS
Required Skills:
Preferred Skills:
Advanced Analytics, Consulting, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Mentorship, Strategic Thinking, Tactical Planning, Technical Credibility
The anticipated base pay range for this position is :
$137,000.00 - $235,750.00Additional 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
How we rate this
Senior Principal Scientist, Data Science - R&D DDSAI - Therapeutics Development & Supply (TDS) at Johnson & Johnson rates 19 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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