Corey J Wade is passionate about mining big data. He believes in accurate statistics and enjoys designing new metrics, like 3NG, the first 3-point basketball statistic to accurately rank shooters by accuracy and volume. Wade has analyzed data for the Berkeley Unified School District, and predicted helpful book reviews using machine learning and natural language processing. He has built machine learning models to recommend books and predict cab fares. Wade’s research, including a piece-wise linear transformation that converts any thumbs-up/thumbs-down system into percentiles with skewness intact, has been published in Towards Data Science and Springboard. A survey of recent projects may be found on his github page.