I’ve long toyed with a mid-life pivot into a different field. Mostly, I lean towards IT as the most practical for me, but I love the idea of finally studying a hard science, which I grew to love, but never really got a good formal education in.

I’ve heard/read, for example, that there aren’t necessarily tons of astrophysics jobs out there, so if you only have a bachelor’s degree, you might have a tough time. I don’t even know that this is true, but I use it as an example.

What are the hard science fields that would be the opposite of this? I could imagine there might be a lot of Chemistry-related jobs, for example, maybe? But I have a hard time imagining what you could do with a pure Physics degree (without also focusing on Engineering or something supplementary)? Would Biology get you anywhere by itself?

Or is it just the hard truth of all hard sciences that you’re pretty much worthless with just a four-year degree, from a job perspective?

  • ivanafterall ☑️@lemmy.worldOPEnglish
    1·
    2 days ago

    Thanks for your perspective, it’s super helpful.

    Was your physics degree a second degree or your first/primary?

    It’s interesting to hear Python was so useful as I’ve wondered whether hiring managers snub their nose at Python (it’s the only language I have semi-real experience in, so far).

    • LetThereBeR0ck@lemmy.worldEnglish
      2·
      11 hours ago

      A BS in Physics was my primary degree (I double majored so I also had a BA in a language that has never been of any professional use to me).

      Python is so ubiquitous that it’s a great tool to know for a multitude of applications, and it pairs well with a physics background since that increases your usefulness as a generalist.

      It is important to make the distinction between a programmer with a hard science/math degree and one with a computer science degree. The former will likely struggle more with building up larger libraries, following best practices for modularity/extendability/backwards compatibility, and other computer science sort of stuff that the latter will ingrain much better. The flip side is that computer science tends to not have as much of an emphasis on a math background, so analysis and Data Science applications often benefit more from the science/math background than the comp sci one (please note that I’m making highly generalized statements here based on what I’ve observed).

      To summarize, if you want to build an app to do something, you want comp sci, but if you want to build a statistical model and have the ability to rigorously validate it and explain what it’s doing, you’re going to need that math background.