[deuslovult]

If you like math, study math. But I don't think refreshing your math skills is the best return on investment if your goal is job hunting.

If you're looking for an ML job, the bar is mostly set by coding skillset and ML knowledge, which is a narrow area of math compared to what you might cover in a graduate math program. That said, it is important to be comfortable with the math that's relevant to ML.

Without direction you could spend a lot of time learning things that aren't going to help in your job search.

[ta46290193]

My impression of ML has been that there are two types of jobs: one, the most common, where you're basically plugging values into tools like scikit-learn or TensorFlow and spending most of your day-to-day fussing around with data wrangling and general software development; and two, the heavy math jobs involving integral signs and Greek letters, which are much rarer and done mainly by people with top-tier PhDs at research labs.

Since at my age going for a Stanford PhD isn't an option, you probably mean by a better return on investment that I should dig into scikit-learn, Hadoop, the current AWS/Google Cloud/Azure options, that sort of thing. Is that right? Which, that's definitely sensible but not exactly what I was hoping for, since it's basically the same as the regular programming I've done, just with a different set of libraries. On the other hand it makes some use of my math background, and perhaps the dream of reliving grad school at a paid job isn't totally realistic anyway.