[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.