The Power of Data Science
Before he came to USF, Vincent Rideout played professional poker, finding the excitement and freedom of the game so much more satisfying than a 9-to-5. Oddly enough, it was through poker that he discovered his passion for data science — gambling is all about probability, and probability is all about data. He returned to school to pursue a bachelor’s in Data Science from USF and loved it so much, he went on to USF’s Master’s in Data Science program. Now, he’s a machine learning engineer at Barracuda, an industry leader in network security that’s based in Silicon Valley. Vincent is excited to apply state-of-the-art machine learning and deep learning techniques to an interesting and dynamic problem space.
How did the Data Science program prepare you for your job?
My BS in Data Science included a focus on computational analytics, meaning that I got to take a bunch of upper division Computer Science courses. Professor Sami Rollins' Loading... course in particular prepared me to deliver the quality of code that’s expected in my position at Barracuda. I also found Prof. Stephen Devlin's Loading... course to be an invaluable introduction to many of the machine learning algorithms I’m using professionally.
Why did you want to major in Data Science?
When I played poker professionally, I also learned about sports betting and was in awe of the ability of bookies to set a betting line that accurately represented the chances each team had of winning the game. How could they distill everything in such a complex system into a probability? Data. I was attracted to the power of data science to help make decisions under conditions of uncertainty and the applicability of its techniques to many different domains.
Why did you choose USF?
My BS in Data Science is my second bachelor's degree. When I applied, USF was one of the only schools in California to accept candidates for a second bachelor's and offer a major that would prepare me for a future in Data Science.
I was also strongly considering USF's Master's in Data Science program (MSDS) and the Data Science undergrad program did a great job preparing me for it. The first five weeks of MSDS are called "Boot Camp" and the name is entirely deserved — it is intense! Between the excellent Probability and Statistics series taught by Professors James Wilson and Nathaniel Stevens and the coding experience I received in R and Python, I had enough familiarity with the Boot Camp topics to succeed.
What are some of your best memories from the program?
The TA for the Probability and Statistics series, Jack Shi, ran study sessions before the exams for those courses. I remember those fondly for being a lot of fun and they were a great help in understanding the material.
Some of my best memories are of Professor David Galles' incredible Data Structures and Algorithms lectures. I've never been so energized and motivated by an instructor. I really looked forward to coming to each and every one of Professor Galles' classes.