Data Analyst (Capstone Project)
Conducted a comprehensive analysis of 5.8 million rows of Cyclistic bike-share data using R (tidyverse, ggplot2) to identify behavioral differences between casual riders and annual members. I executed the full data lifecycle—Ask, Prepare, Process, Analyze, Share, and Act—to uncover that casual riders have 30% longer trip durations on weekends. These insights were used to formulate targeted marketing strategies for membership conversion, with the final findings and visualizations documented in a professional Kaggle portfolio.

