Principal Data Scientist role in AI/ML and optimization within Johnson & Johnson's Innovative Medicine division. The position develops machine learning, optimization, and generative AI solutions to support clinical trial operations, including enrollment forecasting, cost estimation, and site selection across multiple general locations.
Responsibilities
Develop and implement ML, optimization, and GenAI solutions supporting clinical trial operations
Build predictive ML models forecasting operational outcomes and KPIs using operational and real-world data
Formulate and solve multi-objective optimization problems addressing cost, timelines, patient burden, and efficiency trade-offs
Create explainable decision-support systems translating complex analytics into actionable insights for business planning
Mentor junior colleagues on technical methods, processes, and project responsibilities
Requirements
~ Ph.D. in quantitative discipline (computer science, engineering,



biostatistics, health economics, biomedical informatics, or applied mathematics)
~5+ years industry experience delivering ML predictive modeling, multi-objective optimization, NLP, and GenAI projects
~ Hands-on expertise in multi-modal ML modeling and stochastic simulations for time-series forecasting
~ Experience building multi-objective optimization engines using evolutionary algorithms, reinforcement learning, or MILP
~ Proficiency with GenAI and clinical LLMs for document parsing and clinical concept harmonization
~ Proficient in Python, SQL, MLOps tools (MLflow, Kedro), Git, CI/CD stacks, and ML libraries (Scikit-learn, XGBoost, Optuna)
~ Familiarity with clinical operational data, real-world data, EHRs, claims data, and financial datasets

📌 Junior Data Scientist (España)
🏢 Johnson & Johnson
📍 España