Principal Scientist Data Science
About this opportunity
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 Sciences
Job Sub Function:
Data Science
Job Category:
Scientific/Technology
All Job Posting Locations:
Barcelona, Spain, Cambridge, Massachusetts, United States of America, Hyderabad, Andhra Pradesh, India, Madrid, Spain, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America
Job Description:
J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Scientist. The ideal candidate will leverage, adapt, and extend machine learning (ML), optimization techniques, and GenAI techniques to create computational pipelines supporting global clinical operations including enrollment forecasting, cost estimation and optimization, and country/site selection.
J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. 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 J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine
Key responsibilities:
Conceive, develop, and implement ML, multi-objective optimization, GenAI solutions to support clinical trial operations.
Leverage operational, RWD, and cost data to build ML predictive models and optimization engines to 1) predict outcomes of interest, 2) highlight tradeoffs between competing objectives, 3) recommend optimal operational scenarios, and 4) generate actionable insights, enabling early intervention and risk management.
Adapt large language models (LLMs) for tailored information extraction and to create solutions including conducting comparative analytics on clinical trial protocols and trial similarity assessment,
clinical trial data harmonization and standardization,
schedule of activity optimization, and
eligibility criteria evaluation,
Stochastic enrollment simulations to forecast operational and patient journey outcomes including enrollment and study completion.
Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.
Coaches and trains junior colleagues in techniques, processes, and responsibilities.
Required qualifications:
A Ph.D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar),
5+ years of industry experience delivering on data science projects using ML predictive modeling, multi-objective optimization, natural language processing, and GenAI.
Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting.
Experience building multi-objective optimization engines to navigate complex trade-offs using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming.
Experience with GenAI and clinical LLMs for document parsing and clinical concept disambiguation and harmonization.
Proficient in MLOps practices and tools (MLflow, Kedro); Git usage, CI/CD stacks (Jenkins, GitLab) DevOps tools.
Proficiency with programming languages Python and SQL,
Experience with python LLM tools (e.g., DSPy, LangChain), optimization tools (e.g., pymoo) and ML tools (e.g., Scikit-learn, XGBoost, Optuna, PyMc),
Demonstrated experience and familiarity with clinical operational data, real world data, electronic health records and claims, and financial data.
Preferred qualifications:
Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries.
Hand-on experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC and/or EHR to build ML models for estimating operational outcomes or RWE outcomes.
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:
Job details
How this role compares
Computed from every other active Biostatistics & Data Science role in our database, not just this employer's listings.
We currently track 97 comparable Principal Biostatistics & Data Science roles across 18 biopharma companies.
Salary context
51 of 97 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 97 comparable roles
+ 6 more countries
Seniority mix
97 of 97 peers have a known seniority level
Therapeutic area mix
14 of 97 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
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How we calculate "similar"
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Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.