Hello World! I am Jason Lee, the founder and Chief Data Scientist of A.I. Sports, a company carefully crafted to exploit inefficiencies in the sports betting markets. I have years of experience analyzing data in the sports, education, tech, and financial industries. I would like to share some simple tutorials on how to apply data science and advanced analytics in the real world.

Skills

• R
• Python
• SQL
• TensorFlow
• NoSQL
• HTML
• CSS (Stylus, Sass, Less)
• Css Frameworks (Bootstrap, Foundation)
• JavaScript (Design Patterns, Testes)
• NodeJS
• AngularJS - ReactJS
• Git
• PHP
• Google Cloud Platform (GCP)
• Amazon Web Services (AWS)
• MySQL - MongoDB
• Scrum and Kanban
• PowerBI
• Tableau

Projects

• Betting Probability Application - Following the work of Dr. Wayne L Winston in Mathletics and using Rstudio and Shiny created an application to help users understand the probabilities associated with their predicted game line with the actual game line.
• NFL Game Prediction Application - Using Rstudio and Shiny created an application to predict the score of NFL games utilizing two distinct multivariate adaptive regression spline (MARS) models.
• Daily Fantasy Sports, (2014) - Wrote program that scrapes, cleans, and filters relevant NFL and NBA statistics to create my own player projections. Used several machine learning algorithms - neural networks, multivariate adaptive regression splines, random forest, generalized additive models. Then designed an algorithm to generate hundreds of optimized lineups based on point projections, risk tolerance, player exposure, and cost constraints.