Should I focus on general data science or specific platform (AWS, Azure, GCP) for a good career in data science? Which path would has better salary and exit to FAANG?

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To be honest, I don’t see how a platform is relevant to a data science career. Im speaking for someone on more of the platform side, however. In my mind and experience, data science is more agnostic to source, structure, and platform. It never hurts to know a major provider such as AWS, but I’d expect it to be less of a focus from a counterpart on the DS side.

DS folks feel free to correct me

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Cloud providers are only a medium and tool for developing and applying models. DS/DE and other fields of work can be done outside of the cloud. Of course, if you're trying to use their DS/ML tools, you should have some DS knowledge but op doesn't even have that; s/he is trying to ramp up on the cloud and ds all at once.

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Let’s face it, different clients will have different needs. Some people view amazon as their competitor and refuse to use AWS. Your best strategy is to understand the basics and be able to learn differences among them and stay platform agnostic in your development.

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How do you even “focus on a platform” as a data scientist lmao?

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From what I gather from this post you’re more interested in the DS path, so I think you’d probably enjoy ML. But, if you’re early on in your career, try to just get as much exposure as possible. You don’t need to specialize right away.

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One benefit I can think of is that understanding a major cloud platform would be to gain the trust of data that may be replicated to say S3 or another object store.

A lot of DS folk I’ve spoken with have a reasonable preference to work from the true system of record, however this may not always be a viable option for enterprise wide data platforms

I can't see how this would matter. If you know the basics on one patient you can probably figure out any other platform.

Aws if you want to go to amazon

I’ve noticed aws has a large presence in the startups I’ve worked for. They all have similar products so I think as long as you have experience working with the products from one provider you could easily transfer that knowledge over

Majority of faang has their own internally developed tools for data science

If you are talking about data studio it's kinda bad, at least for our use cases. Airbnb's Superset looks neat, but I've never used it.

To your question. Sort of. Our team just wrapped up building a heavily customised shiny front end library. It allows us build applications quickly, with consistent design language and doesn't look anything like what you would expect out of shiny.

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