"I've seen the future of data science, and it is filled with estrogen!" This was the opening remark at a recent talk I heard. If only I'd seen that vision of the future when I was in college. You see, I’ve always loved math (and still do). My first calculus class in college was at 8 a.m. on Mondays, Wednesdays and Fridays, and I NEVER missed a class. I showed up bright-eyed and bushy tailed, sat on the front row, took it all in, and aced every test. When class was over, I’d all but sprint back to my dorm room to do homework assignments for the next class. The same was true for all my math and statistics classes. But despite this obsession, I never considered it a career option. I don’t know why, maybe because I didn’t know any other female mathematicians or statisticians, or I didn’t know what job opportunities even existed. Estrogen wasn't visible in the math side of my world in those days; I didn't see myself as part of the future of data science.
Fast forward (many) years later, and I find myself employed at SAS in a marketing and communications capacity working closely with colleagues who are brilliant mathematical and analytical minds, many of whom are women. They are definitely the future of data science!
Several of these colleagues helped establish the NC Chapter of the Women in Machine Learning and Data Science (WiMLDS) Meetup that just held its inaugural gathering a couple of weeks ago. The Meetup was founded to facilitate stronger collaboration, networking and support among women in machine learning and data science communities as well as grow the talent base in these fields of study. In other words, build the future of data science and populate it with women! The NC chapter plans to host quarterly, informal Meetup events that will feature presentations from practitioners and the academic community, as well as tutorials and learning opportunities.
This inaugural event featured guest speaker Jennifer Priestley, Professor of Applied Statistics and Data Science at Kennesaw State University, who greeted the estrogen-filled audience. She talked at length about the field of data science and the talent gap, and she made the case for getting a PhD in data science.
She said she’s starting to see PhD programs recognize data science as a unique discipline or field of study. She referred to data science as “the science of understanding data; the science of how to translate massive amounts of data into meaningful information to find patterns, engage in research and solve business problems.”
Priestley attributes the rise of data science to the 3 Vs – volume, velocity and variety – across all industries and sectors. She said companies that wouldn’t have classified themselves as data companies a few years ago do now, and they require skilled labor to help them manage that data and use it to make business decisions.
To help fill this talent gap, she talked about the need for PhD programs in data science, but explained that such programs needed to be “21st-century” programs built around applied curriculum. That is how they've built their own Ph.D. Program in Analytics and Data Science at Kennesaw State University.
As I sat in the back listening in, I wondered what would have happened had I been exposed to a network like this during my early college days when I was trying to pick a major and think about a career. Would I have been part of the future of data science? Maybe I’d have made a different decision. Who knows – maybe it’s not too late. It’s certainly not too late to inspire another woman to tap into a supportive network like this.
For more information, visit the NC WiMLDS Meetup website.