Tools: R • dplyr • ggplot2 • lubridate • K-Means Clustering • Customer Analytics Project Overview Customers differ considerably in how recently they purchased, how often they return, and how much they spend. Treating every customer the same can therefore lead to ineffective marketing and missed retention opportunities. In this project, I analyzed 541,909 online…

Overview This project analyzes New York City Airbnb listings to understand the factors that influence listing prices, predict property type, and identify natural market segments within the short-term rental market. Using regression, classification, and clustering techniques, the project connects statistical modeling with practical business insights for pricing, customer targeting, and market positioning. Business Questions Dataset…

A Staggering Daily Reality I was scrolling through X and came across a map posted by data scientist Samuel Sinyangwe. The data from Mapping Police Violence presented a troubling statistic: in 2025, police in the U.S. killed an average of 3 people per day. Link to Samuel Sinyangwe’s Tweet This map prompted me to download…

When we see a headline about an aviation incident, it’s easy to feel a sense of alarm. However, headlines are snapshots, while data is the full movie. In this project, I analyzed over two decades of NTSB (National Transportation Safety Board) records, focusing on large-scale operators to answer two fundamental questions: Which aircraft appear most…