How common is it for companies to hire data scientists while they have no use case or lack the underlying data infrastructure to support them?

I’ve worked as a data scientist at two companies now, the first one was a start up, they had use case at all and my only work was to write project proposals. I’m now at a larger company but they lack the data infrastructure to support the ML use cases that the business requires

Is this common in data science or have I just been unlucky? Should I pivot?

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I think it's common that management doesn't always understand the difference between data science, data engineering, and backend infrastructure.
My advice would be to ask more probing questions during interviews about what they already have in place, what their data environment looks like, what exactly they want you to do, and what other supporting team members will be on the team.

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