From blind trust to budding career
Frankie Zeager started the Master of Science in Data Science (MSDS) program at the Data Science Institute (DSI) with a good deal of blind trust.
“The first time I saw Charlottesville was when I was moving in,” she says. “I had never been to Virginia.”
After graduating from the College of Charleston in 2016 with a degree in economics, Frankie was considering either pursuing a PhD in economics or forging a career in data science. She says she found the Data Science Institute at the University of Virginia after doing “some intense Google searching” and quickly felt like it was a great fit.
“What really drew me to UVA was the interdisciplinary nature of the program,” she says. “Everyone is from a different discipline. We have people who are English majors and people who are the more traditional computer science or statistics majors. When you have a group project, it’s so nice to get all of those different perspectives on the same problem.”
“What really drew me to UVA was the interdisciplinary nature of the program.”
Frankie was also attracted by the tools that were taught and used at the DSI. “We use a lot of free open-source tools like R and Python that are actually being used in the workplace.”
Once starting the program, she found that her favorite classes were data mining and machine learning, taught by Dr. Abigail Flower. (“She’s awesome. She’s one of my favorite professors,” Frankie says.) Model building is what Frankie considers “the really exciting stuff.” And she says, “I think data mining is where you really get to the core of what being a data scientist is all about.”
Gaining hands-on practice has been essential to Frankie in her preparation for entering the field of data science. Her capstone project was sponsored by a bank that wanted the MSDS students to look at credit card fraud detection by using adversarial learning. “We’re approaching the problem from the adversary’s point of view—in this case, the person who is fraudulently charging cards,” she says.
“We’re trying to preemptively change our model to anticipate what the best move is for the fraudster, and that way, we can constantly update our model to predict what the fraudster is going to do next. It’s pretty exciting stuff.”
Frankie says the community of the MSDS community is something she came to appreciate as well. “It’s surprisingly social,” she says, acknowledging that she wondered if her cohort was going to be “super nerdy” before arriving in Charlottesville. She was pleasantly surprised. “We go out for happy hour together, and in our study room, there are always people hanging out and talking.”
As an example of the community focus at DSI, on the night of the 2016 presidential election, the DSI threw a party and hooked up the Data Wall to broadcast various news networks. “There were a ton of people there,” Frankie says, “faculty, staff, and students, and they had drinks and food, so we all got to hang out and watch the beginning of the election coverage.”
Along with enjoying a vibrant academic family, all MSDS students get plenty of hands-on, practical experience, such as giving frequent presentations. The program helped hone Frankie’s public-speaking and project-scoping abilities, which has served her well.
The presentation skills she sharpened at the DSI helped her tremendously in a final interview for a position at IBM Watson Health, in which the candidates had to conduct a rapid-fire group project with people they didn’t know and then give presentations to a panel. But Frankie showed up prepared.
“We do this all the time in every one of our classes,” she says. “So it was really easy to get down to business, because we only had an hour to pitch the idea.”
Frankie rose to the challenge of the interview: After graduation, she’ll be moving to Chicago to work for IBM Watson Health as a data scientist.