[jtcond13]

Writing a full reply since I don't agree with much of the advice given.

I've worked around/in data science teams at a large BigCo and I think that you're far overestimating the bar here. There aren't enough people to who can write data pipeline code (SQL/Shell/etc.), much less implement and intelligently explain statistical/ML models. Also, the average decision maker here does not understand the difference between 'created model in Pandas' and 'created model with Amazon's ML API'.

The modal background of data scientists in industry is closer to 'Econ BA + knows Python' than 'Artificial Intelligence PhD'. Moreover, the former will still enjoy a remunerative career if (s)he's sufficiently savvy about identifying problems and showing off how they can be solved with technology.

There may be a point in time when companies can't get a return by throwing math-savvy programmers at a problem, but that will be long after you and I have passed from the scene.