Victor Hu - Data Scientists at Work - page 250

Sebastian Gutierrez: Why does data science interest you?
Victor Hu: I think there is such an explosion of data in the world today,
and our capabilities of storing and analyzing that data are rapidly expand-
ing. The analytics that accompany data expansion are not quite developing at
the same speed, so there is an explosion of the potential of what products
people can work on, what questions people can answer with that data, and
what industries can be affected. That is very exciting. There are so many
industries where data can make a big difference. That is what inspires me
more than anything else—the way that very traditional industries—finance,
health, public policy, music, sports, just about anything—can benefit from the
intelligent application of data.
Gutierrez: Tell me about the journey from college to major league baseball.
Hu: I studied math and statistics at the undergraduate and graduate levels at
Harvard. For a long time, I wasn't sure what I wanted to do with this skillset.
People always told me, “You can do anything with a degree in math”—which
I think is really funny. I do not know if that is necessarily true. I think you can
apply mathematics in any number of industries, but the approaches are often
similar.
One of my earliest inspirations was reading Moneyball by Michael Lewis. 1 He
brought to the forefront the concept that data was transforming the base-
ball industry. That was one of the earliest instances where I really saw how
powerful intelligent data analysis can be. This was, I think, even before the
term “data science” was really in play. Yet all these people in baseball opera-
tions were coming in and providing very valuable insights that maybe went
against the norm. And, obviously, anytime you try to do that, there is some
resistance. Ultimately, because it was so successful and because there was
this incontrovertible truth that more data leads to better insights, it has now
become a big part of how decisions are made in baseball. Hearing and reading
about that, and seeing how big of an impact you can make in an industry that
I never imagined you could do that in, was very inspirational.
That is how I got into sports initially. I wanted to do a lot of that work and
get in on the ground floor with it. I became an intern with the Yankees, as
one of the two first people they hired to do this type of analysis. It was really
exciting because it felt like the Wild West. Anything was in play—anything
that I wanted to do or they wanted to do was a possibility, and we tried so
many different things. I think that is one of the most exciting things about data
science today.
1 Michael Lewis, Moneyball (W.W. Norton & Co., 2004).