Johnson & Johnson

Principal Data Scientist – DDSAI GD

In short

Principal Data Scientist role at Johnson & Johnson's Innovative Medicine division (Data, Data Science, and AI - Global Development), leading end-to-end delivery of ML, GenAI, optimization, and real-world-data analytics solutions for clinical-development and trial-operations problems in Madrid, Spain. Requires a Master's degree (PhD preferred) and at least 5 years of industry experience leading data-science delivery, with proficiency in Python, SQL, ML, optimization, LLM-development libraries, and MLOps. The role involves partnering with clinical, operational, technology, and data stakeholders, mentoring junior colleagues, and applying responsible-AI and data-quality standards.

# Principal Data Scientist – DDSAI GD
About Innovative Medicine
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries 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.
Job Summary
J&J Innovative Medicine – Data, Data Science, and AI - Global Development (DDSAI GD) is seeking a Principal Data Scientist to lead end-to-end delivery of integrated analytical solutions for defined clinical-development and trial-operations business problems. This role owns solution definition, delivery, adoption, and use-case outcomes across connected stakeholder groups using ML, GenAI, optimization, and RWD.
Key Responsibilities
•Own the end-to-end definition, development, validation, deployment, and adoption of integrated data-science solutions for defined business problems.
•Lead predictive modeling, simulations, optimization, and GenAI applications for study feasibility, enrollment forecasting, country and site selection, protocol design, and operational planning.
•Apply clinical, operational, cost, and RWD—including EHR, claims, registries, and clinical-trial data—to generate evidence on patient populations, treatment pathways, feasibility, and operational risks.
•Lead RWD analytics that inform protocol feasibility, eligibility criteria, recruitment and retention, study design, comparative evidence, and external-control use cases.
•Develop LLM-enabled workflows for information extraction, protocol comparison, data harmonization, clinical-concept interpretation, and targeted workflow automation.
•Partner with clinical, operational, technology, and data stakeholders to frame questions, manage trade-offs, and translate outputs into adopted recommendations and measurable use-case outcomes.
•Apply model-validation, MLOps, documentation, privacy, data-quality, and responsible-AI standards; contribute reusable code, data assets, and technical patterns.
•Communicate methods, model outputs, assumptions, limitations, and decisions clearly to technical and nontechnical audiences.
•Mentor junior colleagues and strengthen delivery practices across project teams.
Required Qualifications
•Master's degree in computer science, engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or another quantitative discipline; PhD preferred.
•At least 5 years of industry experience leading end-to-end delivery of data-science solutions using ML, predictive modeling, optimization, NLP, GenAI, or RWD analytics.
•Demonstrated experience defining, validating, deploying, and driving adoption of analytical solutions that inform clinical-development, clinical-operations, or real-world evidence decisions.
•Hands-on experience with structured and unstructured clinical, operational, or RWD data, including multimodal modeling and time-series or simulation methods.
•Proficiency in Python and SQL, modern ML, optimization, and LLM-development libraries, and reproducible MLOps practices.
•Strong communication, stakeholder-management, and technical-leadership skills.
Preferred Qualifications
•Experience in healthcare, pharmaceutical development, MedTech, clinical development, or clinical operations.
•Experience applying RWD methods to clinical-trial design, including target-trial emulation, propensity methods, survival analysis, or time-to-event analysis.
•Experience delivering analytical products or applications used by clinical or business teams.
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
Compensation
The anticipated base pay range for this position is: €61,800.00 - €106,260.00
Benefits
In addition to base pay, benefits include: an annual bonus with set target (% of pay) depending on pay grade / location, where the actual amount is based on employee and company performance of the previous calendar year, or sales commissions. Also offered: vacation days, parental leave for a minimum of 12 weeks, bereavement leave, caregiver leave, volunteer leave, well-being reimbursement, programs for financial, physical and mental health, service anniversary and recognition awards, and insurance plans (subject to plan terms, and in some locations eligible dependents may participate).

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