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Goodbye, data science

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Re: Goodbye, data science

#341

Post by nerpderp82 »

fnands wrote: post #297
SilverBirch wrote: post #284

Earlier quoted context omitted.

It’s a great skill to walk in to a job and say “hey I’m the expert, that’s not a reasonable proposal, here’s the problem we can solve and here’s what we’ll do”. Much more value to the company, but hard to do.

Yeah I feel a lot of companies could do with running their problems past a consultant first. Also, w.r.t hiring in cases like these, I think often the experienced candidates can smell that this won't be a good gig so don't apply, while the less experienced (or desperate) ones apply. This means the workers get stuck with an intractable problem, and the company gets stuck with workers who are too inexperienced to know…

> even the need, for ____ ________ yet try and hire them anyway.

I think that vast majority of human organizational structures, individuals to large corporations and countries have no clue what they are doing. The most successful apply science and just barely keep their head below the surface by avoiding utter failure. Most people would describe the Olympics as a competition to find out who is the best amateur in a given sport. No, the Olympics is a competition to see who can make the least number of mistakes.

If you are going to make bold dumb moves, you need a whole lot of margin.

Re: Goodbye, data science

#342

Post by wheels »

fnands wrote: post #135
angry_moose wrote: post #72

In a recent past life, I was a HPC (high performance computing) administrator for a mid size company (just barely S&P400) who was in the transportation industry, so I had a lot of interactions with the "data science" team and it was just a fascinating delusion to watch. Our CTO did the "Quick, this is the future! I'll be fired if I don't hop on this trend" panic thing and picked up a handful of recent grads and gave…

Honestly, I can't tell you how many jobs ads I saw where I was wondering: "What would they expect me to bring to the table here?" Some companies just don't have the data, or heck even the need, for data scientist yet try and hire them anyway. Give smart people a fundamentally ill-posed problem and they won't get anywhere anyway.

My ex worked at a startup where she was hired as a the second or third data scientist. Their entire Posgress database dump was 20 MB. And they had three people working full time on analyzing ... that 20 MB.

Re: Goodbye, data science

#343

Post by tasuki »

JoeAltmaier wrote: post #305
tasuki wrote: post #303

Earlier quoted context omitted.

> In real life there's basically one absolute goal, and that's survival. And that's largely assured in developed western countries these days, unless you do something really stupid. Or just get unlucky: no need to do anything stupid. One can easily die of cancer at 30 and leave a toddler behind.

Well, not so easily. The chances per-capita are in the sub-percent range at 30.

Yes, easily. My partner died of cancer at 30 despite exercising, avoiding alcohol, going for the screening, and generally trying her best.

Chances are it won't happen to you and your close ones. Perhaps try being grateful rather than dismissive?

[Edit: perhaps we have a misunderstanding as to the word "easily". I'm not saying it's likely, I'm saying it can and does happen without any warning signs and no amount of planning/preparation can save you.]

Re: Goodbye, data science

#344

Post by nmeagent »

boringg wrote: post #186
mr_gibbins wrote: post #167

Earlier quoted context omitted.

Nope, nope and nope again. I refute this utterly, as a teaching academic. Contact hours at most universities are around 2-4 hours per week per 15-credit module. To gain a degree, you have to take 120 credits a year, typically two terms of 4 x 15 credit modules, or 8-16 hours of contact per week maximum with the entire summer off. You therefore have at least 24 hours a week to study on your own to bring your working w…

No personal attack taken but your experience and points fail to win me over. The difference probably belies in the rigor of the program. It sounds like you are working in a non-engineering based program. In our engineering programs we had 40 hours of class time + lab time per week. I had a concurrent arts degree at the same time which is was, in comparison, incredibly light workload - though concurrently it took time…

> The difference probably belies in the rigor of the program.

This is anecdata of course, but my experience with a top-3 US undergrad aerospace engineering program in the late-90s, early 2000s was around 15-16 hours of class time per week, sometimes increasing to 18-19 or so with labs. Work outside of class was 3x this or maybe 4x around midterms or finals.

Re: Goodbye, data science

#345

Post by johnthescott »

scottLobster wrote: post #156
_jx7j wrote: post #95

Earlier quoted context omitted.

>Meaning you could absolutely suck at your job or be incredible at it and you’d get nearly the same regards in either case. One of the things I don't like about statements like this said in a Data Science context, is that they are true outside of Data Science as well. Executives make big decisions, managers make smaller decisions, nobody can evaluate how good/bad they really were for months or years. Engineers build…

Not to get too off topic, but as a 35 year old engineer it seems the world in general has far fewer consequences than I was raised to expect. Everything from businesses with bullshit ideas flourishing at a loss, to January 6 even being possible (politics aside I expected the Capitol Police to crack a lot more skulls than they did once people started smashing windows), to the whole FTX situation and the tepid response…

stay in your lane, go the speed limit and ALWAYS look for an escape route.

Re: Goodbye, data science

#346

Post by EdwardDiego »

JoeAltmaier wrote: post #305
tasuki wrote: post #303

Earlier quoted context omitted.

> In real life there's basically one absolute goal, and that's survival. And that's largely assured in developed western countries these days, unless you do something really stupid. Or just get unlucky: no need to do anything stupid. One can easily die of cancer at 30 and leave a toddler behind.

Well, not so easily. The chances per-capita are in the sub-percent range at 30.

Unless you're exposed to a carcinogenic chemical...

Re: Goodbye, data science

#347

Post by mattkrause »

3pt14159 wrote: post #259

> Meaning you could absolutely suck at your job or be incredible at it and you’d get nearly the same regards in either case. Story time. There was once a junior data scientist at Shopify that had learned Python and SQL and was tasked to figuring out how to fix their "broken app store recommendation engine" but since they didn't know Ruby, they asked for my help in figuring out what was going on. Well somewhere in the…

Ironically....

Having a subset of totally random recommendations wouldn't be a totally terrible idea---especially if you know which they were! It could help push the system out of local minima and it's the obvious benchmark to beat.

Re: Goodbye, data science

#348

Post by EdwardDiego »

nostrademons wrote: post #182
scottLobster wrote: post #156

Earlier quoted context omitted.

Not to get too off topic, but as a 35 year old engineer it seems the world in general has far fewer consequences than I was raised to expect. Everything from businesses with bullshit ideas flourishing at a loss, to January 6 even being possible (politics aside I expected the Capitol Police to crack a lot more skulls than they did once people started smashing windows), to the whole FTX situation and the tepid response…

Parenting & the public education system is a very artificially constructed bubble designed to reinforce and reward "good" behavior, where "good" is usually defined as "that which makes life easier for my caregivers". That gives kids a falsely inflated sense of how much everything matters: your caregivers want you to mind your behavior, because then they don't have to, even if you would've been perfectly fine playing…

It so happens that "good" behaviour that we seek to embed in our children is generally the same as behaviour that is good for society.

Broadly the values I've tried to instil in my children break down as

- Take responsibilities seriously

- Apply your best efforts

- Be considerate

- Cultivate empathy

- Value yourself

- Don't be a dick

- When you screw up, admit it, and make amends

These, when applied, lead to the behaviours that make parenting easy, and I'm hoping will make them good members of society in general.

Re: Goodbye, data science

#349

Post by hcks »

samvher wrote: post #6

> Nobody knew or even cared what the difference was between good and bad data science work. Meaning you could absolutely suck at your job or be incredible at it and you’d get nearly the same regards in either case. In my experience it's even a little bit worse than that. Approaches that are wrong from a statistics point of view are more likely to generate impressive seeming results. But the flaws are often subtle. A…

> Because these issues are subtle, management will often not pick up on them or not be aware that this kind of thing can go wrong.

Management is not your teacher at school, it is not there to check up your results make sense.

Management mostly assumes you’re competent at your job.

Re: Goodbye, data science

#350

Post by [deleted] »

in9 wrote: post #335
tomrod wrote: post #154

Earlier quoted context omitted.

Agreed. I've run a "data science consultancy" in some form or fashion for three years now. When people say "data science" they mean one of three things: (1) MLE (2) Data Management (3) Data Analysis or Business Intelligence (applications of the same skillsets). (1) has a lot of ongoing innovation, be it in MLOps, autoML, mapping frontier ML to business cases, etc. Innovation is expensive if the investment strategy is…

wow. How you phrase the work and client expectations make seem like working for you is a breath of fresh air in the DS world. Let me know if you ever need a contractor, or let me know how to reach you with a resume :D

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