[DataWorker]

No. A phd in statistics or economics means almost nothing at this point. Even if it did, truly, signal mastery of the content, which it doesn't anymore, it would signal to most people who do this kind of work that you're way overqualified while simultaneously being totally ignorant of the day-to-day work of actual data scientists.

If you want to be a useful data scientist, do a lot of work with data. If you have strong programming skills and are flexible and a quick learner then you will do well.

Spending the better part of your young adulthood getting a phd in statistics, unless you want to go into academia, just makes you look like a fool.

[freyr]

There absolutely are problems that require a more rigorous mathematical training than you get from undergraduate courses or day-to-day experience. Most data scientists and companies may not be tackling these problems, but they certainly exist.

Just having a PhD will open doors for you that would otherwise be shut. But before pursuing that degree, you should be confident that you enjoy working in the field and want to devote your career to it. Also, you have to be prepared to work hard, not just to get the degree, but then to land a job where you'll put that experience to use. Otherwise, you'll be sharing a cubicle with DataWorker and feeling like a fool.

That said, if you don't know whether you need a PhD, that means you probably don't know what kinds of problem you want to work on. And in that case, there's a good chance you'll end up working on a problem that only interests your advisor and nobody else (most PhD advisors have more students than they have good problems to work on). In that case, I wouldn't recommend it.

[Baghard]

I've had complete opposite experience. Do the people who hire for this kind of work often bet on non-PhD candidates? Do they trust themselves to separate the wheat from the chaff?

Don't you want a colleague who is able to mention seminal papers for specific problems? Who is able to read and understand these papers and can distill useful features and optimizations from them?

People with PhD who go into business, usually end up in the better positions. They hire other PhD's for the good positions to keep the signal (mastery of the content) stronger.

As someone who did a lot of work with data I have little problem with my usefulness, but a lot of problems opening doors to the really interesting data companies (lacking a proper academic network). I wish I had gotten that PhD, because right now applying to Google, Microsoft, Facebook, Yahoo or eBay for data science positions makes me look like a fool.

[GauntletWizard]

I've met a lot of fools who've quoted all the right works, in both Computer Science and Data Science. Computer Science fools usually get fired. Data Science fools seem to get promoted to Yes-man status. It's a lot harder to lie about your code than it is with statistics; As the old adage goes, it right behind Lies and Damned Lies.

[threatofrain]

You've said "No", but you haven't countered the posters claims. Are in fact most data scientists PhD/Masters people? I hear the same information at a mid-sized tech company. I also hear similar things about Intel.

[searine]

>Spending the better part of your young adulthood getting a phd in statistics, unless you want to go into academia, just makes you look like a fool.

This is why you are a DataWorker, and not a dataScientist.

Anyone can push bits around. It takes a trained mind to corral them using careful experimentation and observation.