Mark Heiple

Background

About Mark Heiple

I have leveraged my engineering experience, problem solving expertise, and ability to quickly learn new skills by earning a Master's in Predictive Analytics from Northwestern University. I specialized in Machine Learning, Artificial Neural Networks/Deep Learning, Text Analytics, and Time Series Analysis. In addition, classes covered many topics such as R and Python programming, Data Mining, Database design, Predictive Modeling, Clustering, and Visualization. I have extensive experience in a variety of software engineering projects, including reverse engineering, Windows Kernel Device Drivers, encryption systems, cyber security, Windows and macOS application software, and embedded software. In 2012 I had an opportunity to take a sabbatical, which I used for self learning. I explored Macintosh development, which had always interested me. This period of self learning lead to an interest in Data Science. As a result, I enrolled at Northwestern University in the Masters in Predictive Analytics program. During the program, I successfully completed many individual and team projects. I was also invited by a former instructor to work on a volunteer project with the American Association of Variable Star Observers. In November 2018 I was selected as a Finalist for the Class of 2019 Presidential Management Fellows program. I successfully graduated from the program in September 2021.