This is where I showcase my work as an analyst. Each project tackles a real business question and walks through the full analytical process, from data preparation to findings and recommendations. Projects are organized into three tracks: Predictive Analytics, Data Visualization, and Forecasting. Each card links to a dedicated page covering findings, recommendations, methodology, and key takeaways, with reports, slides, and code attached.
Predictive Analytics
Sun Country Airlines: Customer Segmentation
Business question: Who are Sun Country's customers, and how can the airline grow loyalty enrollment and shift bookings to its direct channel?
Applied K-Means clustering to 15,144 customer records to identify 5 actionable segments, translating findings into three targeted campaigns tied to leadership's goals around Ufly enrollment, direct channel growth, and vacation package differentiation.
Predicting Employee Churn
Business question: Which employees are most at risk of churning (leaving), and what organizational factors drive that risk?
Built and compared logistic regression and decision tree models on 4,653 employee records, achieving 79% recall on the churn class and identifying tenure, compensation tier, and education as the primary drivers of voluntary turnover.
Data Visualization
UCI Basic Needs: CalFresh Analysis
Business question: How are UCI Basic Needs Center's CalFresh assistance services performing across four years of data, and what operational changes would most improve program efficiency and student access?
Built a multi-page interactive Tableau dashboard tracking 6,261 CalFresh appointment records across 4 years, surfacing trends in Enrollment Party growth, no-show patterns, student eligibility reach, and seasonality.
Letterboxd: Movies as a Business and a Taste
Business question: What do box office trends and personal viewing data reveal about film as both a cultural and commercial product?
A live window into film as both a personal passion and a commercial product, combining my personal ratings, watchlist, and physical media collection with box office and budget data that auto-updates over time.
Forecasting
Applied Forecast Modeling
Business question: How can forecasting techniques be applied to real business problems across industries?
A collection of forecasting projects from BANA 290, applying causal and time series modeling techniques to real-world datasets. Projects include linear regression, ARIMA, and logistic regression built in Alteryx and visualized in Tableau.