Education: B.A. in Mathematics from University of Arizona M.A. in Economics from University of Virginia
Tell us a bit about yourself.
I currently live in Austin, Texas with my wife, two kids and dog. My education and work has taken me across the country from Tucson, Arizona to Washington D.C. before settling in Austin, Texas. I really like the casual vibe of Austin, and there always seems to be a new unique restaurant to try. I am an active person who enjoys going for a run, swimming laps at the pool and spending time in the garden. I earned a degree in mathematics from the University of Arizona and a master’s degree in economics from the University of Virginia. I have primarily worked as a sales engineer and solutions consultant at both large and small startup companies.
What initially attracted you to the data science field?
I experienced firsthand the amazing things that can be done when data sources (that had been traditionally siloed) were brought together using machine learning and visualizations. I wanted to learn the details of how it all worked.
Why did you decide to pursue a Master of Science in Data Science?
I enjoy learning and have always been a “tinkerer” in things such as coding, arduino, raspberry pi, and even 3D printing. Prior to starting this program I thought about going back to school for a number of years, but nothing really stood out until I realized that I could study this field. It just seemed like a perfect fit given my interests and background.
Why did you choose DataScience@SMU?
I chose DataScience@SMU for a number of reasons. I was kind of nervous with the idea of going back to school and I really liked that I could continue working while attending the program. The main reason though was the interdisciplinary nature of the program plus the fact that it was relatively local.
What skills and tools that the program covers do you think are most appealing?
There is so much to learn in this field, and this program has given me a solid foundation in data science. The most appealing things for me are the ability to take an idea or curiosity and explore it; the statistics I consider to be foundational; and all the coursework around coding (for data mining, analysis and visualization) to generate the results. There is a lot of presenting and writing in this program, which I believe is critical to share ideas.
What do you think about the online learning environment?
There is a lot to be said about being able to walk into your professor’s office and discuss a problem. However, I was really surprised at the intimacy of the online “classroom” experience. I think one of the most important aspects of this program (outside of the effort of the student) is that the professors make themselves available. Everyone is busy these days but in my experience the professors were available. Some are even OK with you texting them!
What do you hope to accomplish with a Master of Science in Data Science?
I hope to build a career in this field and continue to add on to the skills and tools I learned from this program to uncover actionable insights that help drive business value.