John Gilling

Background

About John Gilling

I'm a mathematician, data scientist, programmer, and a musician (in some order). My undergraduate research focused around real and complex dynamical systems, and my graduate-level research included work on complex base systems and group actions on a billiards table. I'm fluent in Python (including numpy, pandas, scikit-learn, flask, etc.), conversational in Scala, and will work in R or Julia if you can convince me it's necessary. I have extensive experience using open-source software and services for processing and analyzing big data (Spark, Snowflake, S3, etc.) I study the practice and theory of machine learning in my free time. I've built an ensemble of Markov Chain models on MIDI note sequences to generate interpolated music, trained a class-weighted SVM to determine whether a given band will perform at a given music festival, and experimented with a variety of deep learning architectures for an array of different classification tasks. Before I made my foray into data science, I worked in education for a number of years, teaching high school mathematics and computer science in Boston, New York and Beijing. As a result, I have a deep understanding of how to convey technical ideas to a largely non-technical crowd. I'm comfortable communicating with people from all backgrounds and I have a knack for pulling out the most important points from a given analysis.