You’re already a Data Scientist, you just don’t know it yet.
Summary: You already have many of the skills you need to move from academia to data science roles in industry — so don’t be afraid to make the switch.
With current events in the world impacting the job market, I recently spoke to a few friends who shared their concerns about the availability of roles in academia. Having just made the transition away from my area of specialization in grad school (genomics) and into the tech industry, I thought it would be a useful exercise for me to write down a couple of thoughts on what the past few months have taught me. If you are in grad school, or if you’re a working professional who is looking to move from a domain-specific role to a more generalist role, here are a few things you should know.
- You already have a background in Applied Statistics.
As a grad student, regardless of whether you studied physical chemistry or cognitive psychology, your training would have included reading a whole bunch of journal papers. And for the past hundred years, almost every experiment in these papers involves some combination of comparing a control group with a treatment group, understanding statistical distributions, and interpreting test results. Without even consciously working on it, you are already competent at an important requirement for data science roles — applied stats.
Think of it this way — imagine you’re on the soccer team at school, and then one day, your friend says she wants to sign you up for a 10K charity run that weekend. Would you assume that your body can’t handle it? You probably run almost ten kilometers over the course of your soccer games and training every weekend, it’s just that you need to remind your body to do it a little differently for the 10K— maybe fewer short bursts of acceleration and quick turns like in soccer, and a more deliberate rhythm during the day of the run.
It’s a similar story with applied stats, you’ve been exercising that muscle for a while now in grad school, now it’s a matter of just fine tuning it to satisfy the interview requirements for data science roles.
2. You have spent time learning “How To Learn”.
No one enters grad school knowing the right tools to solve all problems. Typically, you’re given a somewhat murky project to work on and expected to figure it out — whether it’s part of an advanced course, or a degree-related thesis project. You’re expected to work with minimal supervision, and take the initiative to read up on things, try out a bunch of approaches and eventually arrive at a solution.
This is especially relevant while learning technical & programming skills for data science interviews. Maybe you don’t know how to run that SQL query because you didn’t have to in grad school, that’s okay. Maybe you’ve never used that ultra-specialized data structure, that’s also okay. You have the ability to pick up these skills — back yourself to do so.
I recently watched this video by Mayuko on YouTube, and I completely agree with her — the best skill you can have is the ability (and confidence) to learn new things. And you, my friend, have that skill in spades.
3. For all of Silicon Valley’s disdain for degrees — waving around that piece of paper can make a difference.
Okay, this is not necessarily a transferable skill, but it is definitely an advantage you have from grad school — which is a degree certificate with the word “Master” or “Doctorate” on it. We’ve all heard stories about how you don’t need an advanced degree to break into data science in Big Tech, and I absolutely agree that your technical chops — the ability to train a model or query a database efficiently have no correlation with your degree. However, when a recruiter or manager is trying to make a quick decision between two candidates who have listed similar skills on a resume, the evaluator tends to fall back on the old proxy for “capability”, which (perhaps unfortunately) still means an advanced degree over a bootcamp certificate or an undergrad degree in Data Science, which is still a relatively new concept.
Regardless of everything that’s happening in the economy today, I believe there is cause for hope and optimism in the year to come. Those of us who have had the opportunity to get an advanced degree are in a unique position of having some transferable skills that are in demand in the job market — we just need to focus on leveraging those skills and presenting the best version of ourselves. Good luck!
