Principal Data Scientist, AI/ML and Optimization

What you'll do

• Develop and implement ML, multi-objective optimization, and GenAI solutions to support global clinical trial operations.
• Build predictive ML models to forecast operational time-series outcomes and key performance indicators.
• Formulate and solve optimization problems to balance competing objectives like cost, timelines, and patient burden.
• Integrate predictive modeling with optimization techniques to evaluate alternative operational scenarios and recommend strategies.
• Build explainable decision-support systems that translate complex analytics into actionable business insights.
• Adapt large language models for information extraction, clinical trial protocol analysis, and data harmonization.
• Conduct stochastic enrollment simulations to forecast patient journey outcomes and study completion rates.
• Coach and train junior colleagues on technical methods, processes, and data science responsibilities.

What we're looking for

• Ph.D. degree in a quantitative discipline such as computer science, biostatistics, applied mathematics, or a similar field.
• 5+ years of industry experience delivering data science projects using ML predictive modeling, multi-objective optimization, NLP, and GenAI.
• Hands-on experience with multi-modal ML predictive modeling and stochastic simulations for time-series forecasting.
• Experience building multi-objective optimization engines using evolutionary algorithms, reinforcement learning, or mixed-integer linear programming.
• Experience with GenAI and clinical LLMs for document parsing, clinical concept disambiguation, and harmonization.
• Proficiency in Python and SQL, including specific tools like LangChain, DSPy, pymoo, Scikit-learn, XGBoost, Optuna, and PyMc.
• Proficiency with MLOps practices and tools including MLflow, Kedro, Git, Jenkins, and GitLab.
• Demonstrated experience with clinical operational data, real-world data, electronic health records, claims, and financial data.
• Prior experience in a data science AI/ML role in healthcare, MedTech, and pharmaceutical industries (preferred).
• Experience utilizing clinical trial protocols, registry, cost data, CTMS, EDC, and/or EHR to build ML models (preferred).