‘Changing our world’: Conversations with women in data science

As researchers across Yale continue to probe and ponder the most effective uses for artificial intelligence, machine learning, and massive databases, they’re also mindful of the human element at the heart of data science.

For instance, what are the career pathways for women in data science? What is the work-life balance for young researchers entering this much-in-demand field of study? Who are the role models who can guide the next wave of innovators?

The Department of Statistics and Data Science (S&DS) in Yale’s Faculty of Arts and Sciences and the Yale Institute for Foundations of Data Science (FDS) will examine aspects of these questions in a new series of talks with Yale alumni who are leading professionals in statistics and related fields.

The FDS Women’s Career Development Colloquium Series, which begins at 12 p.m. Sept. 27 with AT&T senior data scientist Elena Khusainova, aims to put top-level practitioners in conversation with students to discuss their experiences and offer guidance.

Yale News recently spoke with the organizer of the series, Ruixiao Wang, a Ph.D. student in S&DS in the Graduate School of Arts and Sciences.

What prompted you to develop this speaker series?

Ruixiao Wang: I was inspired by a conversation I had with a male professor from the School of Medicine and School of Engineering. We were working on a data science project, and he asked if I had a plan for my future. Would I stay in academia or go into private industry? I said I wasn’t certain, but I would probably go outside of academia for my career.

He asked me why. He said, “You have an obvious passion for research. Have you ever talked to any female faculty members or researchers about their experiences?” And I realized I hadn’t.

What do you hope will emerge from the discussions?

Wang: I see this as a great chance for female graduate students to get together and talk with mentors about the challenges we face. How can we help each other?

I want people to get more female perspectives from women who can give us inspiration and confidence as we make these big decisions about our future. It’s never too late to have these conversations.

Let’s talk about your own experience. What appealed to you about data science and related fields initially?

Wang: I started by studying computer science as an undergraduate at UCLA. Then I switched to mathematics because I wanted to learn more about how things function at a more fundamental level. To me, math is something that, once you understand it more, you see that it is the basis for so many other subjects. They’re all based on math.

I began delving more into machine learning when I got to Yale. I could see that both in theory and application, machine learning and AI are changing our world. I want to be part of the latest technologies and ideas that will change the world.

And yet, when I was growing up, I would often hear people say, “Girls should do something easier.” It has kept many women from pursuing these careers.

Beyond the work itself, what other aspects of a career in data science are you interested in talking with women mentors about in this series?

Wang: I want to know how you manage your job and a family. How do you deal with the balance of work and your health? How is that different in different career settings? These are not small things, and I don’t hear enough people in my field talking about them. They’re pretty important.

How did you go about finding your speakers — and how receptive were they?

Wang: I talked with Colleen Chan, a Ph.D. student who graduated earlier this year, and we came up with a list of female alumni I could contact.

They were all so wonderful. Four women responded to me very quickly — the first day. And another two women responded soon after that, so we know we’ll be able to continue this speaker series in the spring. People seem to be very enthusiastic.