Decision Scientist III - Quality and Patient Safety initiative at University of Florida

Location: Gainesville, FL

Cap-Exempt H-1B Position — No lottery required

**JOB NO:** 540285 **WORK TYPE:** Staff Full-Time **LOCATION:** Main Campus (Gainesville, FL) **CATEGORIES:** Health Care Administration/Support **DEPARTMENT:** 29013100 - MD-QUALITY & PATIENT SAFETY **CLASSIFICATION TITLE:** Data Scientist III **CLASSIFICATION MINIMUM REQUIREMENTS:** A Bachelor’s Degree in data science, statistics, bioinformatics, analytics, or similar field and five years of experience; Master’s Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience. **JOB DESCRIPTION:** The **Decision Scientist III** supports the Quality and Patient Safety initiative (QPSi) within the UF College of Medicine by applying decision-science approaches to improve patient safety, care quality, and healthcare operations across UF Health and partner institutions. The role focuses on helping teams evaluate clinical and operational decisions by modeling options, constraints, tradeoffs, and expected outcomes. In collaboration with clinical and technical partners, the incumbent integrates predictive insights, causal estimates, process measures, and operational data into decision-optimization and policy-evaluation work. Core methods include multi-objective optimization, simulation, offline reinforcement learning, and state-space or other sequential decision models. Successful candidates will bring operations research (or related) training and strong collaboration skills in interdisciplinary settings. **About This Role:** Decision Optimization, Offline Reinforcement Learning, and State-Space Modeling - Frame clinical and operational questions as decision problems with clear choices, constraints, timelines, and outcomes. - Develop and evaluate multi-objective optimization approaches (e.g., weighted objectives, constrained formulations, and Pareto-frontier analyses) that balance patient outcomes, quality/value