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Imposter Syndrome (in Data Science)

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Re: Imposter Syndrome (in Data Science)

#2

Post by mykull »

Data science is one of the most imposter-filled "professions". It's a recently-established category of worker that falls across multiple disciplines and is very effected by technological progress. I have met "data scientists" who aren't really good at any aspect of it, but they still get by because of the supply/demand and lack of any existing expertise to say "hey, you know, this person we hired is barely competent and just googles everything we ask of them"

Re: Imposter Syndrome (in Data Science)

#3

Post by sanjha7 »

This describes my situation to the point. I have worked in big unicorns and have deployed many ml based models in production which had moved the numbers significantly while many a data scientists in our team just kept cribbing about errors in data or scarcity of it.

I have no DS background, am a humble engineer but believe it's 10x better to just work with whatever you have available and get sit done.

Re: Imposter Syndrome (in Data Science)

#4

Post by pavelromashkin »

sanjha7 wrote: post #3

This describes my situation to the point. I have worked in big unicorns and have deployed many ml based models in production which had moved the numbers significantly while many a data scientists in our team just kept cribbing about errors in data or scarcity of it. I have no DS background, am a humble engineer but believe it's 10x better to just work with whatever you have available and get sit done.

same here, I haven't explored all nooks and crannies of the "data science map", but all the ml/dl I deployed were a success. I still feel like a major imposter though.

Re: Imposter Syndrome (in Data Science)

#5

Post by gota »

mykull wrote: post #2

Data science is one of the most imposter-filled "professions". It's a recently-established category of worker that falls across multiple disciplines and is very effected by technological progress. I have met "data scientists" who aren't really good at any aspect of it, but they still get by because of the supply/demand and lack of any existing expertise to say "hey, you know, this person we hired is barely competent…

All this means is that we will inevitably reach a point where separate titles are used, and 'data scientist' will means about as much as 'engineer'.

We will distinguish 'machine learning specialist data scientist' from 'database specialist data scientist' just like we distinguish 'electrical engineer' from 'lab systems engineer', for example.

Then, we might have a term for generalists like 'data science technician'. And by then, the people who 'aren't really good at any aspect of it' and can't really function as generalists will be naturally sorted out because they can't really fit into any of those titles

Re: Imposter Syndrome (in Data Science)

#6

Post by natalyarostova »

As a data scientist I have wondered if this field is particularly suited to imposter syndrome. My formal background is economics, and every once in a while I become terrified at how little formal statistics I've studied, or large gaps in data structures etc. although I'm similarly surprised at how far I've gone by just going home and studying the basics when I run into something I don't know, and the gaps in knowledge some coworkers have in areas where I know more.

...although I have met a few genius data scientists who seemingly really can do everything. Although I'm pretty sure they are paid upwards of 300k.

Re: Imposter Syndrome (in Data Science)

#7

Post by dysgathhh »

natalyarostova wrote: post #6

As a data scientist I have wondered if this field is particularly suited to imposter syndrome. My formal background is economics, and every once in a while I become terrified at how little formal statistics I've studied, or large gaps in data structures etc. although I'm similarly surprised at how far I've gone by just going home and studying the basics when I run into something I don't know, and the gaps in knowledg…

I'm pretty certain data science is worse than normal fields. It's probably due to the fact that huge proportion do have PhDs, but that a PhD is not required for the vast vast vast majority of what we do.

So for instance, I totally feel like a data science imposter, but in the last year have done the following: - Pushed a custom deep learning NLP model to production - Created and maintain company's ETL and data warehouse mechanisms - Performed statistical analyses to find ways to better target and increase customer engagement. - Implemented event tracking and performance metrics across products - A sales prediction product that has contributed to $~5M in incremental revenue

Somebody obviously believes in me since I've grown the team from just myself to ~6, but I also know that I've had dozens of past colleagues that would instantly disqualify me since I 1) don't have a PhD and/or 2) can't/don't read statistics/machine learning papers

Re: Imposter Syndrome (in Data Science)

#8

Post by tinymollusk »

natalyarostova wrote: post #6

As a data scientist I have wondered if this field is particularly suited to imposter syndrome. My formal background is economics, and every once in a while I become terrified at how little formal statistics I've studied, or large gaps in data structures etc. although I'm similarly surprised at how far I've gone by just going home and studying the basics when I run into something I don't know, and the gaps in knowledg…

I tend to agree. I think it's because the field uses statistics, which most people have decided are incomprehensible and don't even try to understand. Combined with how bad our brains are at thinking statistically, and you have a powerful desire-for-avoidance by non statisticians.

Combine with the value that good ones can provide, and you have a perfect situation where a boss or peer just thinks thar be dragons in the work sphere of the statistician.

Re: Imposter Syndrome (in Data Science)

#10

Post by mykull »

gota wrote: post #5
mykull wrote: post #2

Data science is one of the most imposter-filled "professions". It's a recently-established category of worker that falls across multiple disciplines and is very effected by technological progress. I have met "data scientists" who aren't really good at any aspect of it, but they still get by because of the supply/demand and lack of any existing expertise to say "hey, you know, this person we hired is barely competent…

All this means is that we will inevitably reach a point where separate titles are used, and 'data scientist' will means about as much as 'engineer'. We will distinguish 'machine learning specialist data scientist' from 'database specialist data scientist' just like we distinguish 'electrical engineer' from 'lab systems engineer', for example. Then, we might have a term for generalists like 'data science technician'.…

You hit me right in the feels, bud.
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