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Goodbye, data science

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Re: Goodbye, data science

#231

Post by wirrbel »

CapmCrackaWaka wrote: post #209
bootsmann wrote: post #128

Earlier quoted context omitted.

I think the issue here is that "data science" encompasses two very distinct branches of work. One answers to business needs and the other produces data based solutions for the product itself i.e you might have a data scientist who A/B tests your website design so you minimize your churn rate and the other is the team at uber eats who maintains the recommendation engine. While the distinction might not always be as sh…

Yes we definitely fall into more traditional "predictive modeling" data science than deep learning / recommendation algo roles.

I think the distinction is not so much on the domain/application. Rather it’s just that many Organisations decided to jump on the data-science wagon and don’t quite know yet for what qualities to look out for during hiring. And in second order as long as the predictive model is not included in a business process the over fitting is not as easily visible to the layperson stakeholders (and junior data scientists).

Re: Goodbye, data science

#232

Post by wheelinsupial »

euix wrote: post #189

I have to agree with a lot of this - I started my career as a data scientist right out of a STEM PhD back when the term just started coming into existence. At the time, anyone who wanted to get hired as a Data Scientist needed to be trained as a professional scientist, i.e. have a PhD - at first my expectation that the purpose of my job was to apply the scientific method to solve business problems by leveraging the c…

> the higher up I climbed the more I realized the job had marginal business impact

Do you have any observations why? I'm a pretty lowly business analyst, but my observation is if you don't own the decision making (usually by having profit and loss responsibility), you can't have much impact. Possibly it's the companies and industries I've worked at, but at the end of the day if the results don't meet expectations, it's the business owner that gets fired and not the people providing the recommendations.

Re: Goodbye, data science

#233

Post by throwaway74829 »

belval wrote: post #113
adamsmith143 wrote: post #73

Earlier quoted context omitted.

If I work my ass off and my model recommends a few extra units, I don't see another dime, so where's the motivation?

Un-ironically: the pride of a job well done? Most people in software on this site a very well paid and well treated, the least we can do is do our job right.

Please speak for yourself. A comfortable cage does not inspire me to go above and beyond.

I very much doubt my "going the extra mile" will really affect anyone at all in any major way. It may make some made up numbers go up -- or down -- but realistically it will have no major effect on anyone at all, except myself (and negatively).

Whatever effect it elicits in another will be short-lived, and forgotten next quarter -- least of all recompensed sufficiently for the sacrifices made.

Re: Goodbye, data science

#234

Post by overgrownzygote »

warinukraine wrote: post #93
jmhammond wrote: post #13

> But there’s also a part of me that’s just like, how can you not be curious? How can you write Python for 5 years of your life and never look at a bit of source code and try to understand how it works, why it was designed a certain way, and why a particular file in the repo is there? How can you fit a dozen regressions and not try to understand where those coefficients come from and the linear algebra behind it? I d…

> But there’s also a part of me that’s just like, how can you not be curious? How can you write Python for 5 years of your life and never look at a bit of source code and try to understand how it works, why it was designed a certain way, and why a particular file in the repo is there? How can you fit a dozen regressions and not try to understand where those coefficients come from and the linear algebra behind it? I d…

I’m surprised I had to scroll so far to find this response.

It was a revelation to me when I realized that, no, it’s not that “most people” lack intellectual curiosity. Their interests are just different than mine.

Re: Goodbye, data science

#235

Post by r-zip »

usgroup wrote: post #153

There are good research jobs in industry which are serious and mathematical. However they also require you to be serious and mathematical. I’d venture to say at this stage that most “data scientists” are either self taught segues from adjacent fields or have a shallow relevant background. The serious places don’t want you… so you end up at the place that can’t tell the difference, and the self fulfilling prophecy beg…

Can you recommend a few such places? :)

Re: Goodbye, data science

#237

Post by mikaza »

I don't see how this personal take generalizes to a trend specific to data science (as much as the term looks weird to me). In other words, I don't see how creating useless Python notebooks is different from over-engineering or creating useless features.

To me the proper context of the story is "cheap money have been flooding the market for _decades_".

Re: Goodbye, data science

#238

Post by ISL »

Can state from personal experience that there exists at least one company where each of the article's leading bullet-points are simultaneously false.

If your DS employer isn't making real use of the capabilities of a skilled data-scientist and that makes you sad, consider looking for a company that will.

Re: Goodbye, data science

#239

Post by anton_ai »

Reading this and other similar posts, I feel so lucky to have found a 1) great boss that really knows his stuff thanks to the fact that he started working on this before it was cool, 2) a great company that believes that data will be the future and 3) a good team that follows me without too many frictions.

Re: Goodbye, data science

#240

Post by asdff »

boringg wrote: post #115
Davertron wrote: post #36

Earlier quoted context omitted.

Well good luck then, in my experience the most free time I've ever had in my life was during college. I squandered massive amounts of that time doing things completely unrelated to education, and I definitely don't regret doing that. College isn't just about book learning after all. But still, BY FAR, college is the time of my life when I had the most free time to do whatever I wanted.

My sense is that your program at school had a light work load - so a difference in experience. My peak workload so far in my life was at college - I had over 40 hours of class time a week which you then have to add on homework, projects and exams. It was a grind. Since then workload has been intense of course but never comparable. I've had much more time to be able to explore personal interests since college.

40 hours of class time a week is absurd
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