[resolaibohp]

I have also found this interesting. What I don't understand is that the amount of data science jobs are no where near the levels that people make it seem. I am not sure where all these people will end up working if they want to be a data scientist. There is not a need to hire huge teams of data scientists like you might for dev roles, it doesn't scale the same way.

[mr_toad]

Every job that involves data in any way is being relabeled a data science job. Most of them are just generating dashboards and posters in Excel or Tableau for people who are data illiterate. I know many people with maths/stats/comp-sci backgrounds who end up in these sorts of jobs.

“Just add a bunch of green up arrows and red down arrows, your manager will love it” was advice from a co-worker of mine. Sadly, she was right.

[wakkaflokka]

It's actually become somewhat hilarious to me. Like you said, the data science label is being applied quite liberally (no judgment, I'm not the world's authority on how it should be applied), so here you have companies paying $100k or more to have people do Excel work or Tableau visualizations.

[toomuchtodo]

"Data scientist" is the new "business analyst".

[kwillets]

I think data science moved into the hole where analysis used to be.

[amrx101]

This. You are exactly right. I work for a startup not in anyway related to Data Science or ML etc. We use Python here. My flatmates work for a big named DataScience company and most of the time its numpy and a bit of data visualisation.Pandas and Numpy to the rescue. I am like dude, I can do that in blink.

[Natsu]

In an engineering class, when dealing with a problem about factories that produce widgets and consume resources/widgets from other machines, I made a complex Excel spreadsheet that was animated to pass little numbers around that represented the items produced or consumed.

It didn't actually give correct results, I'm not sure it could have worked (I needed to do two updates on the same cycle and never did figure out how), and I documented that it was buggy.

But it looked cool and I got good marks. So my experience pretty much agrees with yours.

[PhasmaFelis]

Where can I get a job like that? I'd be happy to take it at this point.

[kwillets]

Data engineering as well.

[madman2890]

Haha, so much yes.

[linuxftw]

Every graduate that doesn't find a high paying job in the field is an excellent candidate for the next level of education.

After you have given a university hundreds of thousands of dollars and a decade-plus of your life, you will then be ready to teach the next crop of students.

[throwawayjava]

> Every graduate that doesn't find a high paying job in the field is an excellent candidate for the next level of education.

1. You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs? No. Not only can 100% of successful top-tier PhD applicants find jobs, 100% of them are strong candidates for the top echelon on entry-level jobs.

If you disagree, go look up the people in Berkeley's CS PhD program. Point out a single person you think didn't turn down mid-100s job offers to attend Berkeley.

Getting into one of these top-5-to-10 PhD programs is no small thing...

2. MOOCs aren't PhD programs and in nearly all cases aren't designed to feed into PhD programs.

3. Finally, at least in CS, at least for the moment, educators are in extremely high demand. And again, at least for CS, that demand isn't being manufactured by the academy.

[gaius]

You really think Berkeley's top-ranked PhD program is recruiting people who couldn't find jobs?

It is well known that PhD programmes churn out far more PhDs than can reasonably be employed in their field.

I mean, including friends and former colleagues I probably know maybe 300 people with PhDs. Of those I can count on my fingers those actually doing research in academia, probably one hand those on tenure track. But do you really think any of them slogged through the programme in Physics or Biology just to get a software job writing CRUD apps, or prettying up BI reports?

[learc83]

You're arguing against a point that the OP didn't make.

[throwawayjava]

See point 3. At least in CS, at least for the moment, there's insane demand for CS educators. Maybe not research track at top 20 R1, but definitely requires a PhD.

[tomrod]

Close to 100%, but not 100%.

[throwawayjava]

This is sort of technically true. Modified statement, based on extensive person experience: ~80+% had such an offer in hand, and the remaining 20% either:

a) didn't bother applying but would've been shoe-ins, or else

b) knew very early (freshman year) they were research-bound and optimized for a non-industry objective function (but could've skated into an industry job of their choice given a shift in undergraduate career focus). E.g., couldn't pass a coding interview and no industry internships but have one or more top-tier publication in a hot subfield.

But (b) is kind of stupid to think about. It's like saying a successful lawyer would not make captain in the military. This may or may not be the case, but either way, who cares?

[olympus]

Lawyers can commission directly as captains in the USAF (and probably other branches) as long as they are not too old and can pass the fitness test. I think they also have to have passed a bar exam in one state, but it doesn't matter which one. They can get up to $65k of student loans repaid and don't even have to go through the same basic training as everyone else.

So (b) is slightly less trivial than saying a successful lawyer would not make captain in the military because most lawyers are one conversation, a few signatures, and one oath away from being a captain.

So don't delay lawyers, join today!

[fapjacks]

Did you actually do any recruiting? Or are you like me and just sort of started inadvertently talking this way after a certain number of years?

[throwawayjava]

Yes, I know, that was my point.

> ...So (b) is slightly less trivial

I'd argue not. In both cases, a fully capable and prepared person has to jump through a couple of relatively trivial hoops. And when those hoops aren't possible to jump through it's a weird case. We can split that hair, but it's silly.

[telchar]

You chose a funny example. A lawyer can make captain in the military just by signing on the dotted line, same with a doctor.

[linkmotif]

It’s a pyramid sceme you can get in on with financing.

[eksemplar]

I disagree with this. Every enterprise company has an analytical department, even more so in the public sector. My municipality has 8 guys working on analytics for instance.

They are mostly economics or (I’m not sure what it’s called in English, but it’s a degree in societal administration), but they really ought to be data scientists because everything they do is based on huge sql data sets.

We pay private contractors a lot of money to turn our data into cubes and manageable models because none of our analytics know how.

In 10 years I suspect anyone with that job title will need data science on their resume. Not just to manage the data, but also to start doing machine learning on it.

By comparison we have one network guy to run the network for 10.000 employees and 5000 students, with a backup guy who knows everything the first guy does but works with something else, you know, in case the first guy quits.

[gaius]

My municipality has 8 guys working on analytics for instance.

Do you propose that they should take a MOOC like this one, or that they should be replaced by MOOC graduates?

[eksemplar]

I think they’ll be replaced with candidates that mix economics and data science as they naturally retire or go elsewhere. If I was young in the field I’d definitely take a degree in data science, especially if I worked in the public sector where we’re much more willing to pay for your education as well as give you time off to take it.

[itronitron]

I actually think in order to do it right you need to have a sizable team (n > 7) of data scientists in order to keep them honest, productive, and developing their skills. They will need to pair up with a team of software devs/ML/data wranglers to help them push the edge on what they are doing. Depending on the company that could be the complete engineering team, or it could be a disjoint set.

[hkmurakami]

Rebrand marketing into a data science'y name to attract quantitatively minded applicants (already starting to happen in some orgs)

[telchar]

As someone in data science this isn't a trend I particularly like. I suppose to some extent these jobs can be filtered out by requiring a salary that they're not willing to pay for that work.

[booleandilemma]

I don’t think the colleges care where their students end up when they’re done with them.

[cossatot]

They care to the extent that the alumni are willing and able to make fat donations.

[codingdave]

Startups do not need a huge team of data scientists... but industry in general does need data analysts and this would certainly enhance the skills of that crowd.