Depends on what data scientist is within an organization.
Alot of times, it means "the guy who does crap in SPSS or needs Tableau".
Why Are Data Science Leaders Running for the Exit?
71–80 of 102 posts
Re: Why Are Data Science Leaders Running for the Exit?
#72The dissing of PhDs is unwarranted. Gross over-generalization. People being skeptical of ideas in a peer-review sort of way can be both good and bad. For example, the assumptions and claims of this article can do with a substantial amount of skepticism. Perhaps someone should express skepticism and view this article with the peer-review critical eye that he mentions. I am reminded of climate-change skeptic articles t…
Also, the idea that peer review is rife with people killing articles to save their "pet theory" is idiotic. Reviewers just want you to cite them.
Ideally, reviewers would just want your paper to be as good as it could be.
And yes, we should all appreciate not just the named author of the work, but all of the work that goes into it. This is true of all works, not just studies.
Re: Why Are Data Science Leaders Running for the Exit?
#73Science progresses at the speed of a funeral.
Re: Why Are Data Science Leaders Running for the Exit?
#74Earlier quoted context omitted.
> The author is way off base in saying software engineering is about assembly rather than discovery. Depends. The interview process that is the fad these days selects for assembly workers. Organizations using that process are doing so to find people who aren't curious about broadening their knowledge and experience, but to find people highly competent at repeatedly doing their CS curriculum over and over. > On an unr…
> Organizations using that process are doing so to find people who aren't curious about broadening their knowledge and experience, but to find people highly competent at repeatedly doing their CS curriculum over and over. And why are they doing this? Why don't they just buy an existing solution from another vendor, why build your own solution?
Because such products typically don't exist (either they aren't appropriate for the scale or the end use, or both).
There's a definite place for these workers.
Re: Why Are Data Science Leaders Running for the Exit?
#75Earlier quoted context omitted.
A major point that's underappreciated in academia is quality of execution. The more complicated a model is, the less well you can execute it. Academics are rewarded for building complicated things, but it often takes graduate PhDs entering industry a long time to learn about quality of execution. I think that's the fundamental tension between business and academia.
I wanted to say that I disagreed with you, but then I realized I don't know what you mean by "execution" here, though. This statement "The more complicated a model is, the less well you can execute it" is fishy though. The typical problem in practice with complicated models is the data quality and quantity to support it, not the implementation or interpretation. I suppose here we also need to define "complexity" - I…
I took "execution" here to mean "scaling up". In a trivial case, a model may fail to scale up if it's computationally too slow or too sensitive to noisy data. Sometimes these shortcomings cannot be tested in a laboratory environment with limited data sets.
Re: Why Are Data Science Leaders Running for the Exit?
#76The dissing of PhDs is unwarranted. Gross over-generalization. People being skeptical of ideas in a peer-review sort of way can be both good and bad. For example, the assumptions and claims of this article can do with a substantial amount of skepticism. Perhaps someone should express skepticism and view this article with the peer-review critical eye that he mentions. I am reminded of climate-change skeptic articles t…
Not to mention, saying that PhDs are underprepared to lead. Which the article then jumps to essentially saying, "hire the MBA".
That is a recipe for disaster - non-technical people leading technical people. Maybe we should hire an MBA as VP of Engineering too?
Re: Why Are Data Science Leaders Running for the Exit?
#77As someone (a Director) running for the exit... lack of control over: taking on new projects, staffing, infrastructure, meeting schedules, deadlines. Complete lack of ability to say "no" to our biggest client. Add in conflicting priorities from leadership, month long delays in compensation adjustment, lack of clarity around valuation status, and having to focus primarily on new and maintenance ETL work.
I got frustrated enough to where I almost quit on the spot a few weeks ago. Frustrated enough to b on the verge of tears and punches because I felt I'd wasted the past two years of my life. I worked to get myself transferred from my leadership role to, ostensibly, a more thought leadership type role which should happen in next few weeks.
However, if I don't see significant changes in January, February, and March then I'm leaving. Honestly, I'll probably leave anyway because I think I can grow my skillset, work on better problems, and set my future up better somewhere else.
What I hate about this situation is that I used to be the biggest supporter this company had. But years of this difficulty is enough.
Re: Why Are Data Science Leaders Running for the Exit?
#78Earlier quoted context omitted.
Until recently I led a Data Science team (manager and IC) at a non-software Fortune 10. I, and everybody else on the team, left within a year of joining. The division where I was in hired me to grow both Data Science practice and the team. The company was enormous, so there were data science teams all across the company, all operating in silos. The biggest problem can be summarized like this: If you want to run your…
Thank you for this comment. I joined a non-tech company as their first data scientist, and am now tasked with building up the data science efforts of the company. Your comment is really ringing true, though I've found the company here to be generally great to work with in terms of their flexibility. Funny enough, it took me months of working with the IT department to get a VM with 8-cores and 64 GB of RAM, or the abi…
I work for a large consulting firm that does both of these activities (data engineer/analyst delivering rapid value + long-term data scientist / architects engineering fully integrated solutions connecting ML to business process) and I can say without a doubt we get much higher feedback from the the former than the latter.
Most businesses think small. I'm not even sure it's about risk/reward, either. I think people really don't have vision especially when it comes to technology and more specifically data.
The next generation is coming, though.
Re: Why Are Data Science Leaders Running for the Exit?
#79I've never seen a "data scientist" produce anything meaningful, at least at my company. They run some data through some Python framework and produce weird meaningless numbers that I'm supposed to be impressed by or to trust. No insight as to how that number came to be. "87.525%". Ok sweet. Could've come from /dev/urandom for all I know. At least 3 of them have left in the 2 years that I've been here. It seems like 90…
I don't think data scientists are thinking about "Big $$$".
I think many of them are PhD students who are leaving academia, voluntarily or not, and data science is a logical first job.
Re: Why Are Data Science Leaders Running for the Exit?
#80Earlier quoted context omitted.
I'm sorry but a standard t-test is like the most basic thing in statistics after means and variances. It's not like they want you prove the CLT or something. To me it's more like a statistics fizz-buzz.
To which, of course, the correct answer is "Unless you have good reason to believe the data is normally distributed, you should be using Mann-Whitney", then explain that :-)
Excuse me, I think that at this juncture a Kruskal-Wallis would be more appropriate (assuming multiple distributions).