Rajvi Shah

Maintained accurate prescription and insurance data to reduce billing errors and speed up claims turnaround. Performed inventory analysis and demand forecasting to improve stock availability and reduce shortages.

Analyzed 5,000+ real-world emergency department visits per year across two hospitals to map patient flow and identify operational bottlenecks. Built and evaluated predictive models and delivered Power BI dashboards to support early discharge planning and care roadmap decisions.

Projected 20-year MRI exam demand using population growth data and scenario modeling to support long-term equipment and staffing capacity planning. Documented assumptions, data sources, and methodology for stakeholder review.

Built a predictive model for hospitalization duration using 6+ patient variables to improve interpretability and reliability. Implemented a SQL-driven data pipeline and delivered interactive Power BI dashboards with bed-allocation recommendations.

Gathered and documented business requirements for a wearable-integrated in-app heart risk predictor by translating clinical risk factors into model features. Built and tuned an XGBoost classification model with ~92% held-out prediction accuracy.

Built KPI reports and dashboards from clinical and operational data across two hospital systems to support performance improvements. Supported faster data-driven decisions through consistent data collection, cleaning, and Excel-based reporting.

Grade: GPA: 82%

Completed a Post-Baccalaureate Diploma in Health Analytics with coursework in R, SQL, Power BI, machine learning, and statistics. Earned a GPA of 82% and was on the Dean's List (Fall 2024).

Grade: GPA: 3.75 (Meritorious Student)

Completed a Doctor of Pharmacy degree with a GPA of 3.75. Recognized as a meritorious student.