Andrew is transitioning to data science after spending 5 years modeling policy impacts for think-tanks and consultancies in Washington, DC. His educational and career background has been focused on energy efficiency, environmental sustainability, and physics. Andrew is a skilled communicator and excels at explaining complex topics in a manner that is simple and easy-to-understand. He is particularly fond of the Random Forest model, which he considers to be the “Ask the Audience” lifeline of Machine Learning algorithms.
