Data Science Is America’s Hottest Job

Those kinds of jobs are advertised as “data science” jobs. In fact any job that involves data manipulation at all is getting re-branded as “data science”. Partly this is employers doing a bait-and-switch to attract better candidates and partly its just jumping on the bandwagon.

But candidates aren’t entirely innocent either. How many programmers - an honest title for honest work - call themselves Senior Certified Enterprise Solution Architect Team Thought Leaders or some such nonsense? We’ve all met a few. LinkedIn is crawling with them.

1. A little bit of the selfish "oh no, the secret's out, at what point is my salary going to drop when the demand is met by the dedicated Master's degrees and bootcamps?"

and

2. These articles seem so incredibly corny, it's almost embarrassing. The "hottest job"? Ahhhh, stop it. But these things go in an out of phase, similar to back in the day when "anesthesiologist assistants" (CRNAs, AAs) were the hottest thing for Bloomberg to talk about. It will not last forever.

The irony is that I probably only knew "data science" (always in quotes) existed because I read one of these cheesy articles. I mean, we all know that statistics have been around forever, but that there were dedicated positions where you could run stats, build models, and then deploy them all in a single role was foreign to me.

So it's a combination of a potentially irrational fear of self-preservation, and laughing at the state of affairs where some basic stats work will pull in that kind of money.

I tend to have fears about the future, always wanting to hedge myself so I don't become outdated. In the data science sense, I see the field becoming super super broad and eventually saturated with new supply, so I debate on whether I should pivot into management of analytics in general or not. I.E. getting my hands off the keyboard. Ultimate goal would be to help define, strategically, how statistics/data mining/machine learning/yada/yada/yada are used at a company.

In my case, I'm a reasonably solid R / Python programmer (who occasionally dabbles in racket, clojure, and others). I've got the sort of applied statistical training of someone who took a quant-heavy course load in a PhD program. I've even (by title) been a data scientist a couple times now.

Having recently decided to reenter the job market, I'm reminded that finding the RIGHT data science role is a major challenge. When someone wants a data scientist, they may be looking for someone with a lot of specialist depth in operations research, financial forecasting, machine learning, data-focused software engineering, or some other not-at-all-universal area of expertise.

In some ways, I almost think that someone with a bootcamp level understanding of stats may be at an advantage. Whereas I'm very inclined to be, "Oh! You want this other kind of person. Would you like me to put you in touch with one?" I think someone more junior is inclined to be "How hard can [X] be?"

I did a MOOC, nothing wrong with them. A lot of it turned out to be just revising things I had originally learned in my BEng or MSc, but I learned some things too. And a bit of revision never hurt. I don’t think I had done much calculus “in anger” since graduating for example, so that was rusty.

In 5 years or 10 years there will be no data scientists as a full time job - the skills will just be folded into regular programming jobs or accounting jobs or whatever. If you’re in that job now, make hay while the sun shines