apohn

7 ms·

1.
by apohn 3y ago
While I generally agree, I think there's a point in these 2 statements that can easily misinterpreted. >It is likely that the Data Scientist role is in a long term decline... Also > Data science is in decline and vaguely defined
2.
by apohn 3y ago
>With 10+ years in DS, I've always felt that best DS were always basically software engineers that knew math and were more interested in prototyping cool machine learning product than maintaining production infrastructure. Unfortuna
3.
by apohn 4y ago
There might be a lesson from history on where an "AI" startup needs to focus if they want to succeed. Starting around 2012, there was a huge hype around ML. Lots of startups on selling "ML." If you look today, the majo
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by apohn 4y ago
One of the ways I think about this type of problem is by asking "You want to use computation to extract a signal from this data. What's that signal worth to you in business ROI dollars?" If Domain Expertise + Feature Enginee
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by apohn 4y ago
>This couldnt be further from the truth. I think one thing to keep in mind is that there are specific use cases where the cost of using DL isn't worth the improvement in accuracy (if there is one) from a business ROI perspective. I
6.
by apohn 4y ago
>But (especially in Enterprise B2B) they're not coders, and they're not product managers, and they are not quite salesperson "enough" to qualify for evolving to any of those career positions. I was in PreSales for a l
7.
by apohn 4y ago
>Probability Through Problems First time I'm hearing about this one, thanks for the recommendation. Unlike Calculus or even a typical one semester Statistics course, probability is one of those topics where you need to see a lot of
8.
by apohn 4y ago
In the last 5 years I've moved from Data Science Manager to Principal (IC role, but basically the external facing technical lead of the team) and now Senior. When I add up all the positives and negatives at work and at home, I think I
9.
by apohn 4y ago
>But it also (1) helps keep bad content off of the platform, so users aren't exposed to it, (2) lowers the number of human reviewers who come into contact with it, which is improves their jobs, and (3) frees up budget for whatever i
10.
by apohn 4y ago
>But I also think there's a lot more opportunity in using statistics/ml/data science in the top line than most companies practice. I consider myself a fairly honest Data Scientist, in the sense that I like it when I can ma
11.
by apohn 4y ago
>I genuinely do not understand the logic of cutting this team to save costs. I've been in a situation where a company was under pressure, was trying to make a big pivot, and there where multiple rounds of layoffs. At one point I cou
12.
by apohn 4y ago
It's possible to have teams that save millions of dollars a year and not be worth it to keep them. For the sake of argument, let's say a statistics team has 5 people. Cost of Employee at FB, including insurance, office space, 401K
13.
by apohn 4y ago
I work in the field of Data Science and one upsetting reality has started to sink into my mind over the last year. In a business there is top line and bottom line. There are a lot Statistics/ML/Data Science jobs that are about mo
14.
by apohn 4y ago
IMO the reason behind this is that a lot of "data science" driven decisions are short term decisions. So you can look at something on a PowerPoint, not really care if it's wrong unless you personally will get fired if it tur
15.
by apohn 4y ago
IME, this is the difference. Data Engineers are the people who take raw data (e.g. what lands in S3) and put that into data systems that can be used by other systems (e.g. Dashboards) and people (e.g. Analyst, Data Scientists, BI people).
16.
by apohn 4y ago
>One extremely frustrating aspect of plant meat is that they tried to aggressively push out traditional veggie burgers on restaurant menus. The homogenization of veggie burgers into one particular type of patty is the reason I don't
17.
by apohn 4y ago
>I'm happily doing mostly data engineering + stakeholder management instead of hyperparameter tuning. Agreed. I actually like that in DS you can have a job where you are involved in the end-to-end of a business problem and that you
18.
by apohn 4y ago
>Where will that leave people trying for either ML engineer or more data analysis focused DS roles? Or even just everyday utility scripting/automating powers? Can even the latter two can be largely replaced by hybrid finetuned multi
19.
by apohn 4y ago
IME the core issue here is that there are far more SWE jobs than ML/DS jobs, which leads to a far greater variety of SWE jobs, which means people are better able to find SWEs jobs where they are able to find a job that matches their jo
20.
by apohn 4y ago
>The last thing I want to do with my time is read data science and ML blogs and newsletters which are guaranteed to be 95%+ crap that's either irrelevant to me, wrong, useless or plagiarized from something I've already read. Ar
21.
by apohn 4y ago
I've also seen a new title called "Applied Scientist." I think at a particualar FAANG company (I don't remember which one), Data Scientist = Insights+Reports, Applied Scientist = Building Data Pipelines+Models, and ML E
22.
by apohn 4y ago
>I’d rather work on a project that builds something and the effort accumulates into something more tangible than an analysis report. Before deciding to become a Software Engineer I'd recommend you think about what that "somethi
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by apohn 4y ago
>For the greater world I'd say definitely. Could you elaborate? I honestly don't understand... The effects of subprime crisis was not limited to the US. And instead of people not being able to afford homes, there were lots of
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by apohn 4y ago
>Opendoor: "the most challenging real estate market in 40 years” Didn't the subprime mortgage crisis happen in 2007? The current situation is worse than that???
25.
by apohn 4y ago
You are correct that if you are unemployed and looking for a job it doesn't matter. All you see is increasing competition in the job seeker market and that sucks. But it does matter for people who are employed and looking for jobs. I
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by apohn 4y ago
It's hard to understand if this is actually related to layoffs based on larger market forces, or just a once a year house cleaning. I've worked at places that laid people off once a year. It's a common way to give managers a
27.
by apohn 4y ago
>But it's still a human making a decision in the end I've got a story here from a previous job that illustrates this. I used to be part of an Analytics and Forecasting team at a well known non-tech company. It's a global
28.
by apohn 4y ago
Boom and Bust in everything, including hiring. It's just that nobody knows how long the boom and bust last, but when you're in the boom take advantage of it.
29.
by apohn 4y ago
>How did you determine that the market is fine I didn't say the market is fine. I said it's not as bad as one might think based on social media. I lived through the .com crises and the mortgage bubble. People in my neighborho
30.
by apohn 4y ago
>I’m about to enter the job market, and I’m terrified You're getting a highly biased view of what is really going on in the job market because some high profile Tech companies laid off people. Their leaders are not liked so everybo

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