Do you need a graduate degree for data science?  Maybe so. Maybe not.

Jeremie Harris Dec 18, 2018·8 min read. Toward data science

“I’ll level with you: I’m a PhD dropout.

 

I’ve gotten a lot of mileage out of that title, by the way: it hints that I’ve done a lot of grad school, but still maintains the aura of badassery that only the word “dropout” can provide. In some ways, it’s the ultimate humble brag. Graduate with a PhD, and you’re one nerd among ten thousand. But drop out 2.5 years into it, and you’re an edgy nerd. People will wonder what other edgy shit you might to do next. “Elon Musk dropped out of grad school,” they’ll say. “This guy could be just like Elon!”

The advice I’ve given here is unconventional in many ways. But in a rapidly developing field like data science, convention can often lag considerably behind what’s optimal. As a society, our perception of the value of graduate education is one of the aspects of conventional wisdom that’s most badly in need of catching up to reality.

So take it from a former academic-turned-startup-founder: not all degrees are for everyone. Here’s why.

 

1. The PhD

If your goal is to become a data scientist or machine learning engineer/researcher, a PhD *might* be a good move. But there are also two big reasons why it might not be:

1. It takes a REALLY long time to get a PhD.
2. You’re unlikely to learn anything of value unless you get the “right” PhD from the “right” supervisor.

To the first point: in the U.S. or Canada, a PhD takes anywhere from 4 years to 7 or 8 years to complete. The median time to completion is usually 5 or 6 years, depending on the institution. Now let’s put that into perspective.

You know what wasn’t a thing in data science 5 years ago? Spark, XGBoost, jupyter notebooks, GloVe, spaCy, TensorFlow, Keras, Pytorch, InceptionNet, ResNet, reinforcement learning (like, basically at all), etc, etc.

To the second point: take a moment to think about who would be supervising you, and why they aren’t already working at Google or Facebook.

 

2. The M.Sc.

Do you need a Master’s to do data science?

 

3. The undergrad?

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