After taking Data 8 as a freshman, Subhiksha Mani discovered the potential of data science to drive discovery. Now a senior, she plans to major in Data Science with a domain emphasis in Cognition. Subhiksha shares her thoughts about the growth of data science at Berkeley, her internship at YouTube, and the upside of uncertainty.
This interview was condensed and edited for clarity.
How did you first get interested in data science?
I first became interested in data science after taking Data 8 as a second semester freshman. I loved that data science equipped me with the skills to learn about many other fields by working with data sets from the biological sciences, social sciences, humanities, and various other fields. I came to Cal with a desire to study Molecular and Cell Biology, but later found that I enjoyed working with data and seeing other fields like cognitive science or genetics from a data science perspective.
Why do you want to major in data science?
I really love the idea of studying how humans make decisions. A key component is how humans infer ideas and knowledge from data sets. Data science offers a quantitative look on how decisions are made.
What will your domain emphasis be?
Definitely the Cognition domain emphasis. I love learning about how the human mind works and I believe pairing data science with cognitive science is a super powerful combination. It allows me to continue learning about how humans make decisions and carry these findings into the data science sphere to analyze.
What’s the most interesting data science project you’ve worked on?
I would have to say a project from my internship this past summer with YouTube in Cambridge, Massachusetts. I can’t really go into too much detail regarding the project because it’s confidential, but one of the best parts of the experience was that even though it wasn’t inherently a data science project, I was still able to take the skills that I learned from school and then leverage those skills to benefit a software engineering project.
How do you see using data science in your future?
I’m still trying to decide where I want to go ⏤ whether it be in data scientist roles, product management, or software engineering, but regardless of the field I choose, the fundamental skills I’ve gained from working with data applies to all of these fields. Knowing how to work with data and make data-driven decisions are key strengths that most individuals in the tech field should have, and I think data-driven decision making is very key to any of these three areas.
What do you think is the most important ethical consideration in data science?
I definitely see privacy in data as a crucial struggle that we are currently facing. We need to be cautious about whose information we are dealing with and we need to make sure we don’t expose individuals. It basically comes down to being aware of your user and protecting their identity.
What’s the most interesting thing you’ve learned about data science?
The most interesting thing to me is how rapidly data science is actually growing. I definitely saw this firsthand, because when I took Data 8 as a second semester freshman in Spring 2016, there were only a few hundred students in the class. Now I’m a TA for the course and there are around 1,300 students. I’ve been on the Data 8 course staff for five semesters ⏤ two semesters as a tutor, and three as a TA ⏤ so I’ve seen how quickly the class itself has grown. Some people are saying data science is just the new fad, but I think the most important thing is that there’s so much interest in the field, and if we leverage that interest properly, so much can be done. These students have an interest in working with data or using that data to help the world at some point, so I think we can take that interest we see on campus and channel it in the right way in order to get the most out of it.
There’s so much interest in the field, and if we leverage that interest properly, so much can be done.
Sometimes you might not know what you want to do, and I think that uncertainty is great because it pushes you to explore different options. And from there, deciding what you like is equally as important as deciding what you dislike because it in a way makes you more sure of the decisions you make.
When I came into Berkeley, computer science and the whole "techy" environment was much of an outside world to me, but it was really exciting. It was a lot to navigate as a freshman, but over time I have learned through my experiences in classes I’ve taken and projects I’ve worked on, that you know, it’s all about improving your skills. Regardless of where you start out, over time you will gain new skills and you will see improvement.