Teaches at General Assembly
Riley is a software engineer in Austin, TX. He graduated with a degree in Marketing from Texas A&M University, which led to a job as a roofer. He quickly realized he needed a marketable skill and started selling websites to small businesses while simultaneously learning how to code. In 2008, he learned Ruby on Rails in order to turn his idea for a web app into a reality. ChubbyGrub was the result, and has been featured on LifeHacker, The Consumerist, and CNBC.com. Recently he made the transition to Data Science, finishing in the top 13% of the 2017 March Madness Kaggle Competition.
In recognition of his exemplary service in the classroom, Riley has been selected as a member of General Assembly's Distinguished Faculty program.
Tim is a lead data science instructor for GA’s enterprise clients in Washington, DC. He recently escaped the world of consulting, where he worked in litigation analytics helping lawyers win cases with data. Prior to his work in industry, he earned his Master’s degree in statistics. His graduate research focused on statistical programming and machine learning, something he’s still passionate about today. His motivation for teaching is to make the things he finds interesting just as interesting and accessible to everyone else.
When not thinking about programming or math, Tim spends his free time reading sci-fi/fantasy and theorizing on how to construct the perfect omelette. He plays a mean game of pool, too.
In recognition of his exemplary service in the classroom, Tim has been selected as a member of General Assembly's Distinguished Faculty program.
ADIWID (BOOM) DEVAHASTIN NA AYUDHYA
Prior to joining GA, Boom worked as a quantitative analyst at BlackRock covering over $42 billion of High Yield bond portfolios. Boom is a graduate of DSI-6, where he was excited to add Python to his skill set and build a portfolio of machine learning projects to aid his transition from quant finance to tech. Since completing his capstone project on optimizing rideshare ETA predictions, he has been working on a predictive model to help ridesharing companies anticipate driver churn rates. In his free time, Boom can be found exploring restaurants in NYC and SF if not thinking about what to do next with his sous-vide cooker.