[qubex]

I didn't treat it as trivial (exactly) but I oozed what I judge a suitable level of condescension for what is clearly a very venal question that transpires a very narrow horizon. As for the ”it's called ’statistics’” comment: it is, and that subject has a rich history going back centuries — much of the ’modern’ ”data science” is just a less refined, more brutal reinvention of those same techniques.

[nl]

I run a data science team.

We have statisticians (yes, plural) on my team who have published in Nature, and plenty with other backgrounds.

Even ignoring the data engineering side, there is plenty that statisticians don't do or know which is useful data science.

Take the two attitudes to p-tests, or what a "reasonable number of features" means. You drop the Jeff Dean "consider training models with billions of features" quote on a statistcians desk and see their eyes open.

Statistics is great, but data science is just as much programming as it is stats.

[samuraixp]

Awesome, so what qualifications do your Data Science team members have and would you hire someone without a degree? Or what if they had a data science / ML / AI MOOC like Udacity or Coursera? And do you have any advice for OP or others who don't have degrees?

[nl]

We've interviewed people without degrees for SWE positions. I don't think we've hired any.

I wouldn't rule it out, but it would be useful to have accomplishments to point to, or a personal recommendation.

We have a stack of maybe 25 well qualified PhD data scientists waiting for interviews. It takes a lot to get to the head of that line.

[tutufan]

Interesting. So perhaps tales of shortages are bullshit?

[nl]

It's pretty hard to find people who know how to apply the tools that they have to new problems.