Honest question: is ML/DS something you can just pick up and be hired[0]? May be I'm ignorant, but I'd think employers would look for a degree in some related field to actually consider you for a position doing it.
[0] As in how you can pick up web hacking, do a few websites and create a reputation and get hired that way without a formal degree.
There was a thread on here a month or two ago about this. In general, it was noted that it's best (for both employment as well as just getting stuff done) to have a deep understanding of a particular area of ML rather than a general understanding of many areas. Usually those with a deep understanding have focused on it in school. But the latter group of generalists is a much larger group in the software industry, since most of us did not go to school for this specifically.
I went from being a US diplomat with no coding background to getting a job at edX as a machine learning engineer, so it's very possible. The keys are to find projects and build a portfolio so that you can prove your capabilities, and to start a blog/go to meetups so that you can build an audience and find opportunities.
Market seems to want a lot of them, different profiles and CVs for different domains and responsibilities: data wranglers, data analysts, statisticians, machine learning, business analysts, communicators, infrastructure operators, big data architects. The best shot is coupling your academic / self-matured strength with a domain you really like and start building your own portfolio from real-world case studies in the field you choose.
I think you kind of posed a question and a partial answer. If degree in related field (math, statistics) then yes you can pick these things up. If CS or no degree it will be much harder to pass resume filters.
[0] As in how you can pick up web hacking, do a few websites and create a reputation and get hired that way without a formal degree.