Graduate student in Business Analytics, with prior experience organizing large volumes of unstructured data and project work applying Python, SQL and Tableau to public health, healthcare and automotive questions.
Built machine learning models to predict which homes in Flint, Michigan were most likely to have dangerous lead service lines.
Delivered the analysis and final report as part of a four-person team.
Integrated two datasets that could not be joined directly by building a demographic aggregation strategy, then engineered features and trained Random Forest and Linear Regression models.
Analyzed U.S. elderly healthcare delivery across demographics, income, access and outcomes, then assessed how Patient-and-Family-Centered Care can be implemented.
Compared market share across manufacturers to see how position shifted over time.
Built and deployed a market intelligence dashboard presenting sector movements and catalyst summaries.
A number is only useful once someone can act on it.