So you’re considering careers outside of academia, and you’ve heard all the data science hype. Sounds like a pretty good gig, doesn’t it? But because data science means different things to different people, it can be hard to figure out just what you should do now to prepare yourself for a job as a data scientist after you graduate.


Conveniently, data science isn’t very different from graduate research—in fact, there are some small but important ways you can change your time in grad school that will make you feel like you’re already a data scientist by the time you graduate. I’ve had a lot of fun taking this approach for the last year and a half, and I’m feeling pretty good about my job prospects once I graduate in December. Plus, many of the steps I explain here are also applicable to other non-academic careers, especially in the Bay Area tech scene. (Take all this with a grain of salt, though: I don’t have a job lined up yet!)

With no further ado, here are 10 things I’ve done during grad school to become a data scientist.

1. Start early. This is a long list and most of the steps take time. Plus, the sooner you start thinking about this stuff, the sooner you can decide if data science is a good fit for you. Better to find that out before you get the job than after!