Data Challenge Winner Sophie Bair – a Role Model for Women in STEM
Sophie Bair from Columbia University tied for 1st place in our recent Back to Campus Data Challenge. She is one of two very impressive women in STEM who topped the scores of hundreds of participants from around the nation. Read about how she did it and get to know the young woman behind the top score – you’ll be inspired!
Columbia University undergraduate student Sophie Bair recently achieved the remarkable feat of beating out hundreds of Back to School Data Challenge participants, the majority of whom are pursuing a Master’s Degree in Data Science or Computer Science. Sophie is pursuing “only a B.A.” (her words) with a double major in Statistics & Neuroscience.
Sophie is the recipient of half of the $1000 scholarship prize, having tied for first place with another participant, Jie Han of University of San Francisco, another woman hoping to join the ranks of future data scientists.
We interviewed Sophie at Columbia to find out a little more about the person behind the top score. Following is a summary of our discussion.
Have you participated in data science challenges before?
Look out Kagglers! Shockingly, this top scoring undergrad is just getting started competing in data science challenges. Sophie had never entered a data science challenge before the QuantHub competition. But Sophie does have a history of competing at the academic level in high school math and physics competitions. Reflecting upon her decision to enter the challenge she reasoned,
“I really like competitions and I kind of miss that.”
So she decided that the QuantHub Data Challenge was a good opportunity to see how her skills measure up. (Turns out they measure up just fine!)
How did you learn about QuantHub’s Data Challenge?
Sophie received an email from Columbia’s Data Science Society. She was familiar with their hackathon and so decided to give the Data Challenge a go. We’d like to give a special thanks to Columbia’s Data Science Society for spreading the word. It paid off because Columbia also had the highest average score in the Data Challenge and will receive a $1000 grant for the university!
How does it feel to beat out over 500 top students? And as a female undergraduate student?
“Wow, it’s insane. I can’t believe it. My mom was an English major so she’s just like ‘you didn’t get that from me!’”
Sophie explained that of course she is excited to be a kind of role model for young women. She’s even thinking that in the future she would like to make it her mission to “help women advance by using data science.” She is ecstatic about tying with another woman, emphasizing the rich and often forgotten history of women in Computer Science fields.
How did you become interested in data science?
“Well, I’ve always been kind of a nerd in that way, even as a kid. My family still makes fun of me for this, but literally the day after Halloween I used to sit down and make a graph of all the types of candy I got.”
Sophie went on to explain that she continued pursuing this passion for math and statistics throughout high school. She says this is the reason that she chose to double major in Statistics at Columbia, adding “I didn’t want to lose touch with my love for math.”
For a while, that passion was overshadowed by her love for neuroscience, but she is looking to get more in touch with her quantitative roots after realizing her favorite part about research was analyzing the data once she obtained it. Similar to the way she was enchanted by the freedom and possibilities of academic research, she now loves the idea of developing data science skills that can apply to many different projects in vastly different fields.
“There’s just so much we don’t know about the brain and how it all works. The possibilities to learn are endless. “
What did you think of the Data Challenge and how did you approach it?
(Laughs) “Well it took me a LONG time to do it, like, 2 days!” She adds that since she knew she had a few days to complete the challenge, she went about learning the things she did not know in order to finish it. She explained that while she had learned Python and a lot of the methods used in the challenge through the research that she did over the summer, she had to teach herself new concepts over the weekend to be able to solve the Challenge problem that she’d received.
“I spent a TON of time learning, which I loved.”
She added that by the time that she submitted her answers, she felt pretty good about them, but she did not think that she would win.
Tell us about your research projects at Columbia’s Yuste Lab.
Sophie conducted research as an Amgen Scholar in the Yuste Lab on Columbia’s campus this past summer and presented her findings at UCLA’s Amgen Scholar symposium. The Yuste lab’s stated goal is “to decipher the neural code, i.e., the relation between the activity of neurons and behavior or mental states, by understanding the function of the neural circuits.”
Sophie explained that it’s difficult to come up with novel yet feasible research topics. In this project, she worked on decoding how our brains store auditory memories by conditioning mice to associate certain tones with rewards.
In past projects, she has worked on mouse models of schizophrenia to figure out why schizophrenic patients are not as good as healthy people at detecting novel tones after hearing a series of the same tone repeated. Through advanced statistical techniques, her team found that there is a specific cluster of neurons responsible for this “deviance detection,” and are working to figure out why/how this is disrupted in schizophrenia, as well as possibilities for manipulating this through optogenetic methods. (Wow.)
Do you have ideas for future research that you’d like to do?
Currently the Yuste lab is conducting neurological research using Hydra, organisms with simple nerve systems. Sophie explains, “hydra are very cool because they’re one of the only organisms that you can dissolve completely into single cells, and they can come back and reform an entire system. They raise a lot of interesting questions as to why and how early nervous systems first formed.”
That said, Sophie is contemplating a move out of research for a while to get a taste of working in the “real world” with others. She explained,
“Research can be isolating, and in order to be successful it feels like you have to deeply specialize in one thing. I would rather apply my skillset to a variety of fast-paced projects where I can see tangible effects, ideally for the benefit of other people.”
To this effect, Sophie has taken a new job that she will start soon working as a Database Manager with Community Impact, a program on campus that provides ESL and high-school equivalency services. She’ll be using data science to help determine the effectiveness of the program’s methods and classes, and assist with using data to help with the grant-writing process.
In an exciting future move Sophie will be heading to the University of Amsterdam to do a semester abroad. “I was a bit hesitant to go for it” she explains, “because I was afraid I might miss out on job opportunities and fall behind in what’s going on in my field. However, I think the great thing about data science is there’s so many amazing online resources and opportunities for independent projects that I’ll never have to stop learning, even while I’m abroad.” She is looking forward to this new and potentially life changing experience.
Your stated dream job was “to use data to help people”. Can you expand upon this goal?
“I’d really like to figure out a way to use data science for good. Data and its proper use and access has become a really scary question lately, but I believe there’s an enormous untapped potential to use it to help people.”
To this effect, Columbia has a program called “Data for Good” which Sophie says she wants to get more involved with. The program provides students with opportunities to work on some really important topics, such as human rights violations and poverty eradication.
Sophie says her ultimate dream would be to use data science to help women in some way, as she is a passionate feminist and activist, especially when it comes to women in STEM.
Now for the big question, what are you going to do with your winnings?
“Well, I have really curly hair and I’m thinking about splurging a chunk of it on a really nice haircut at a salon specializing in curls.” Alas, Sophie, in New York, that’s about as far as $500 will take you!
True data scientist skills demonstrated
In summary, we’d like to highlight a few things that we learned about Sophie Bair that we feel are required to be a top data scientist.
- Strong at math – Sophie chose to pursue a double major in statistics to continue developing her love and talent for math and statistics.
- Curiosity – She has chosen a field of study and research projects that allow her to explore big questions that remain unanswered. She has also chosen to study abroad in a country she has never been to.
- Problem solving – Unhindered by her newbie data science challenge status and knowledge, Sophie taught herself what she needed to know over a weekend in order to solve the Data Challenge.
- Challenge seeking – Even though she has already won competitions and received scholarships and awards, Sophie chose to do the Data Challenge as a new learning experience.
- Creativity – In addition to coming up with novel, unexplored research ideas, Sophie is thinking about creative ways to apply her data science skill set in the future.
We wish Sophie the best in her future travels and endeavors and hope to see her name back on the leaderboard for future data challenges!