Allison Hegel won a scholarship to Metis' Live Online Intro to Data Science course through Women Who Code's weekly publication the CODE Review. In this article, we explore her aspirations, her dreams, her experiences at Metis, and how she plans to use that opportunity to achieve her goals.
What do you do day-to-day for work/education?
I’m just finishing up my PhD in English, where I’m working on a project analyzing book reviews on sites like Goodreads and Amazon. Data science is making its way into lots of unexpected fields like mine, and it allows us to look at a much wider range of books and a more democratic sample of opinions than we have in the past. It’s great to be able to switch between reading a theory of the internet in the morning and coding in the afternoon!
Why do you like being a technical person? What misconceptions do people have about tech?
I’m wary when people see tech as a magic solution to the world’s problems. We technical people have some powerful tools at our disposal, but those tools come with plenty of problems of their own. The more we are willing to question what our computer spits out, the better.
What is a major challenge you've faced in tech?
Documentation! So many of the latest and greatest methods and packages are poorly (if at all) documented or use tons of jargon, which makes it tough for people who are learning to pick them up and deal with the many errors that inevitably pop up. I’ve really come to appreciate clean, well-documented code, and I’ve vowed to make sure my own projects make sense to people who aren’t me.
Have you helped others overcome challenges in tech?
Most of the people I work with are on the humanities side rather than the technical side, but whenever I can, I try to serve as a translator and intermediary between the “two cultures.” It’s actually really difficult to be able to explain technical things clearly, but it’s probably the best way to truly learn something. I think that humanists have lots to teach tech people, and vice versa, so I really value my role in bringing the two together.
Any tech pro-tips? Any tips for people who want to follow the kind of path you've had?
Learning data science takes time! I’ve been extremely lucky to have a flexible schedule as a graduate student, but there have still been plenty of late nights staring at cryptic error messages when nothing seems to be going right. I would suggest taking lots of breaks, but most importantly building a community of people to learn with so that moments when you’re stuck become moments you can reach out to other people and know that you’re not the only one struggling, and you’ll get through it!
What most excites you about your career and what you're hoping to do in Data Sci?
Data science touches everything we do these days, not just online but also behind the scenes, in who gets offered loans or admitted to college. I hope that in my career I can bring a humanistic perspective to this mathematical field, and try my best to understand the human impact of data science decisions.
What was your experience learning at Metis like?
The Metis Data Science course was the most interactive online course I’ve ever taken. The instructor and TA made the class feel like we were all in the same room, and we built up a really supportive community over the six weeks. This made learning a huge amount of material much more manageable.
What project did you work on for your Metis course (provide some details please)?
I had a blast applying what I learned in the Metis course to real data. I chose the Yelp Open Dataset to work with because I was interested in what kinds of attributes people value most in a business. I built a regression model to predict a business’ star rating using its attributes, like whether it caters or has bike parking. You can check it out here.