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"
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.
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.
I enjoyed this Partially Derivative podcast where two of the podcasters discuss their experience with imposter syndrome