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Genuine question: why is there so much pure teeming hatred for data scientists in this comment thread? Almost every comment comes off as full of snark and vitri

Genuine question: why is there so much pure teeming hatred for data scientists in this comment thread? Almost every comment comes off as full of snark and vitriol against data scientists.

astrophysician 6y ago
I'm guessing just venting personal frustrations due to their own experiences, plus maybe poor hiring and guidance of data scientists in their own teams? I have definitely seen DS people in my experience that fit some of the descriptions here, but I think it's a mistake to trivialize the DS position itself. A good DS is a valuable asset, but depending on your company/data, maybe not worth the cost. Plus there is no "single" DS candidate or role, a lot of these roles (data engineer, DS, analyst, swe) blend together at times, and it's about finding the right balance of skills. Sometimes I think a company (not having the DS experience themselves) mistakenly over-hire DS roles in today's hype of "AI" when their data is mostly run-of-the-mill and only requires simple linear models that can be architected an understood by a stats/math-savvy engineer. Even then, a good DS is still useful (even linear models can be complex: e.g. what priors do you want to use? Do you want a multi-task solution? etc.), but maybe not worth the cost.
bartleby_ 6y ago
Probably just people blowing off steam and the target de jour are data scientists. If people had to sit down with their company's data scientists to air their grievances face to face I doubt they would be so condescending.
danbrooks 6y ago
I would guess that it's a reaction to job title hype. There's a huge variety in DS responsibility and background between companies.
andrewnc 6y ago
I came to this thread interested in the discussion, but I feel now like the homer simpson meme retreating into the hedge. Maybe I'll come back in a few hours, but for now I'll stay away.
lottin 6y ago
Yes, the tide is turning now... who came up with the term "data scientist" anyway? It's a made up profession. If you need someone who understands statistics, get a statistician, or maybe a mathematician. If you need someone that designs and writes computer programs, get a computer programmer. But a "data scientist"? No, thanks.
- worik 6y ago
  Exactly
bart_spoon 6y ago
It tends to happen any time something becomes trendy. Data science has/had a lot of hype over the last decade, and people seem to have an inherent tend to want trendy things to fail. Combined with that, you have a bunch of people hopping on the data science bandwagon, so you get a lot of grifters, snake oil salesmen, or simply individuals whose output is poor quality. Seems to have created a feedback loop, where there is always a new example of some AI solution failing, or a data science initiative that didn't work out that everyone can point at and say "See! I always knew this trend was dumb!". Reality is that data science is here to stay. It's coming out of the honeymoon period, and things may never be as hyped up as it has been the last decade, but that's probably a good thing for the field. Everyone will probably move on to hating the next up and coming thing. I have a hunch it could be something in data engineering because, while not exactly new, it is absolutely the next "data science" in terms of demand, and with products like Snowflake having so much hype behind them, it seems the backlash will be inevitable.
mywittyname 6y ago
I think a lot of people feel like data scientists get all the credit and the fun work, while we have to do all the heavy lifting and boring stuff that they need. There's this idea that data science is a special and unique skillset that couldn't possibly be possessed by a simple software engineer. Despite being largely a subdomain of CS. I remember an era before "data scientist" was a job title. When we (programmers) would analyze data to see if we had enough information available to identify the problem, if not, fix that, then come up with a strategy to solve it, test, and finally deploy the model. The fun part was trying different solutions and analyzing the data. It also felt awesome to deploy a product that worked like "magic." Product owners didn't know or care what a neural net was, they were just happy it worked. Now there are tons of data scientist out there who take the easy, fun, rewarding work and try to skip over the nitty gritty implementation details. Then management thinks engineering is incapable of doing such work, and the only time we get the opportunity to do something fun is to do so behind the scenes.

Genuine question: why is there so much pure teeming hatred for data scientists in this comment thread? Almost every comment comes off as full of snark and vitriol against data scientists.

astrophysician 6y ago

I'm guessing just venting personal frustrations due to their own experiences, plus maybe poor hiring and guidance of data scientists in their own teams? I have definitely seen DS people in my experience that fit some of the descriptions here, but I think it's a mistake to trivialize the DS position itself. A good DS is a valuable asset, but depending on your company/data, maybe not worth the cost. Plus there is no "single" DS candidate or role, a lot of these roles (data engineer, DS, analyst, swe) blend together at times, and it's about finding the right balance of skills. Sometimes I think a company (not having the DS experience themselves) mistakenly over-hire DS roles in today's hype of "AI" when their data is mostly run-of-the-mill and only requires simple linear models that can be architected an understood by a stats/math-savvy engineer. Even then, a good DS is still useful (even linear models can be complex: e.g. what priors do you want to use? Do you want a multi-task solution? etc.), but maybe not worth the cost.

bartleby_ 6y ago

Probably just people blowing off steam and the target de jour are data scientists. If people had to sit down with their company's data scientists to air their grievances face to face I doubt they would be so condescending.

danbrooks 6y ago

I would guess that it's a reaction to job title hype. There's a huge variety in DS responsibility and background between companies.

andrewnc 6y ago

I came to this thread interested in the discussion, but I feel now like the homer simpson meme retreating into the hedge. Maybe I'll come back in a few hours, but for now I'll stay away.

lottin 6y ago

Yes, the tide is turning now... who came up with the term "data scientist" anyway? It's a made up profession. If you need someone who understands statistics, get a statistician, or maybe a mathematician. If you need someone that designs and writes computer programs, get a computer programmer. But a "data scientist"? No, thanks.

worik 6y ago
Exactly

bart_spoon 6y ago

It tends to happen any time something becomes trendy. Data science has/had a lot of hype over the last decade, and people seem to have an inherent tend to want trendy things to fail. Combined with that, you have a bunch of people hopping on the data science bandwagon, so you get a lot of grifters, snake oil salesmen, or simply individuals whose output is poor quality. Seems to have created a feedback loop, where there is always a new example of some AI solution failing, or a data science initiative that didn't work out that everyone can point at and say "See! I always knew this trend was dumb!". Reality is that data science is here to stay. It's coming out of the honeymoon period, and things may never be as hyped up as it has been the last decade, but that's probably a good thing for the field. Everyone will probably move on to hating the next up and coming thing. I have a hunch it could be something in data engineering because, while not exactly new, it is absolutely the next "data science" in terms of demand, and with products like Snowflake having so much hype behind them, it seems the backlash will be inevitable.

mywittyname 6y ago

I think a lot of people feel like data scientists get all the credit and the fun work, while we have to do all the heavy lifting and boring stuff that they need. There's this idea that data science is a special and unique skillset that couldn't possibly be possessed by a simple software engineer. Despite being largely a subdomain of CS. I remember an era before "data scientist" was a job title. When we (programmers) would analyze data to see if we had enough information available to identify the problem, if not, fix that, then come up with a strategy to solve it, test, and finally deploy the model. The fun part was trying different solutions and analyzing the data. It also felt awesome to deploy a product that worked like "magic." Product owners didn't know or care what a neural net was, they were just happy it worked. Now there are tons of data scientist out there who take the easy, fun, rewarding work and try to skip over the nitty gritty implementation details. Then management thinks engineering is incapable of doing such work, and the only time we get the opportunity to do something fun is to do so behind the scenes.