Alison Tuiyott [honors junior major in Statistics, Class of 2020]: The Center for Analytics and Data Science hosts the DataFest, and so I've heard about it, I've heard about it at work, at home, and I was just like, "Hmm, I wonder what this is." And so some of my peers are also huge data science people and statistics people, and so one of the questions was, "Are you participating in DataFest?" That was one of the biggest talks, and as a freshman, I was like, "Oh, not really. I don't really want to do it." But I ended up getting a team together. Other people were like, "Yeah, sure, we might as well try it." And then we didn't do so well our first year!

A lot of cool things happened, and we all came together, and we presented, and then when they said we'd won, I just, you know, was in awe. Because I came from being the freshman who was just like "I don't really think I can win," to now, as a second year, I'm like, "Yeah. Our team actually is talented enough to do this," and so I was really, really excited.

One of the big ideas of the problem was can you help them — the specific company we're not allowed to say — can you help this specific company answer some business questions? They would give you like leading questions, but it's just the way, our idea was just like, everyone would probably go with whatever the leading question was, but how can you think outside of the box and think of a different perspective on the question? And I think what our team did really well was thinking like, "OK, yeah, they'll give you this and this sort of format, but how can you twist it and maneuver your way into thinking about it in a different way?"

What really helped us is that we're all basically math and stats people, but everyone has their own thing that they're really good at. For example, I would say that I'm better at presenting, getting in front of people, talking about what we did, and then there are some people on the team that were just good at coding, just like hacking away. If we had a question that we wanted to answer, we'd just be like, "Hey, can you answer this question in terms of looking up in the data what the answer would be?" Then we had some people that were good at thinking mathematically. You know, analyzing the data was all about thinking, yeah, about the theorems we'd done in class but how can you apply them in real life.

I think one of the best things is being able to communicate, bridge that gap between statisticians and business people, because I think that's one of the biggest hardships we face as statisticians, is being able to communicate exactly what research we did, and so one of my favorite things to do is just think about it in layman terms. And, you know, if you can just speak to a person like you are right now, but now explaining a concept that's really meticulous and detailed, that is the biggest selling point.

And so by surrounding myself with these four strong individuals, I was able to just keep learning and keep understanding, you know, build off what I already know, and I think that was what was amazing, and I want to continue doing that in the future — surrounding myself with people that will help me grow up, like in terms of knowledge and statistics and just in general in my career, because these are people who are bringing you up versus you bringing everyone else up.

[April 2018]