At Beth Israel Deaconess Medical Center/Harvard Medical School, I developed predictive models to identify risk factors for patient attrition and support clinical decision-making.
I built interactive Power BI dashboards to track KPIs across treatment centers, and designed research-ready databases for cohort analysis using claims and EHR data.
As a Research Teaching Assistant at Center for Collaborative and Interdisciplinary Research, I mentor students in survey design, visualization, and statistical analysis using R, Python, and NLP tools.
Earlier, I built Azure Data Factory ETL pipelines at Women in Data and a Python recommendation engine at Alliant Infotech. My work spans healthcare, workforce, and product analytics, including A/B testing, causal inference, and machine learning.
