Regarding this point, for the transition from STEM academia to industry data/software:
You’ve spent years developing the relevant skills. However you **absolutely must package & frame the skills in ways that industry folks can appreciate.** https://twitter.com/emily_brier_/status/1360692246476128258

Recruiters won’t know the names of your telescopes (besides Hubble maybe) or care about your hydro simulations. They will never read your list of publications.

You need to show them in ~2/3 of a page that you’re a more intriguing candidate than someone with a bachelor’s in CS.

Talk fewer details about the simulations, and more about your role in developing the code. Did you write it? Did you collaborate on a code base?

Talk less about the astro phenomena the data came from; more about what you did with it. Clean? Pipelines? Analysis? Visualization?

And familiarize yourself with the tools and jargon in the industry.

There’s a big difference between not knowing them, and being able to say in a screen call “Yeah I’ve been playing around with AWS, put some practice data in S3. Lately, I’ve been trying to learn Sagemaker…”

“Oh your team uses GCP and not AWS? I haven’t used GCP yet but I’ve read about the recent ML features on it that use SQL syntax. It’s on the list of things I want to learn.”

Years of research + team collaboration + rigorous analysis + familiarity w the kinds of tools out there + some experience using them…

That’s a formula that can make you competitive with the CS majors. But you have to build out the latter pieces, and polish the resume & pitch.