I turn raw data into insight and raw ideas into experiences — bridging analytical rigor with visual storytelling.
I'm a student at the University of Michigan studying Information Analysis, with a focus on data-driven storytelling and human-centered design. My work spans Python data pipelines, statistical modeling, API integrations, and CMF (Color, Material, Finish) design.
I've worked across customer-facing roles at Apple and State Farm, led teams as a Project Manager at 100K Ideas, and collaborated on research projects that bridge technical analysis with real-world impact.
Cross-platform analysis comparing artist popularity between Spotify and YouTube. Built a SQLite database from two APIs, calculated engagement metrics including views-per-listener ratio and average views per video, and created visualizations for the top 25 artists. Conducted at University of Michigan for SI 206.
Statistical analysis of 10,000 records across 20 countries exploring whether coffee consumption impacts stress, sleep, and BMI. Applied chi-squared testing, OLS regression, and XGBoost classification with SHAP feature importance. Key finding: sleep hours, not coffee, was the strongest stress predictor. SI 385 at University of Michigan.
CMF and product marketing work developed through Pensole Lewis College of Business & Design in partnership with Nike, and brand strategy projects at the University of Michigan.
Open to internships, collaborations, and creative projects at the intersection of data and design.