The net result is that you might end up in a BD-type analyst role, which may not be bad depending on your goals. It wouldn't really hit the engineering target, though.
What will probably happen is that the pool of "data science" jobs will grow, but the bottom half won't be real DS.
I don't mean to imply that a person can become a decent data scientist overnight. It takes years, but it can be done.
On Wall Street this sort of role is called a "quant", although there's less machine learning in finance than one would expect (hard to audit). "Data scientist" is a startup quant. Just as with quant jobs, some firms will only hire PhDs with research experience, while others will take chances on smart people without it.
I'm arguing that it's more serious than this: there are so many PhDs out there right now, companies will have no lack of skilled, well-credentialed candidates to choose from. Going down the "do it yourself" DS route is thus (a) very difficult, and (b) not very likely to pay off.