* or substitute whatever other enterprise framework you want
...because that's all that most business require, 99% of the time. To you know, get things done and make money and stuff.
Which may not fit your needs, but why be "depressed" about it? It's just the way things are in the commercial world.
If you want someone with more fine-grained stills, try articulating that in your job postings. What we see, all the time, are ads mentioning platform X, with no articulation whatsoever as to where, even on some approximate logarithmic skill, they'd like the skill level and comfort with platform X to be.
And in the few firms that actually do have real engineering trade-offs that favor the use of those types of frameworks, they tend to hire people who are well-suited for the role, and then create job functions surrounding them that are respectful of aptitudes and skills of the people they hire.
In most firms that adopt these frameworks (for status effects), they are just desperate to fill seats and increase engineering headcount. They don't respect your skill set or even care if it matches the business need. They just need to get you in the door, and then find a way to deal with inevitable dissatisfaction later.
Welcome to the real world.
For those positions, I am sure that smart full-stack developers could easily pick up the statistics for data cleaning and quickly gain a passable understanding of the models consumed from APIs in a black box way. In fact, full-stack devs may be happier in these jobs due to the visualization and database components.
A much smaller subset of data science is actually focused on solving novel business problems and may centrally focus on deeper knowledge of a given technique, like MCMC methods, deep learning, real-time classifier systems, etc. For these, you do tend to need more significant experience with the specific machine learning tools being used (or enough general skill in statistics to pick them up quickly). Smart people of all stripes could still learn that stuff, but it's a lot harder to see them being able to convince a firm to hire them in that capacity.
The second type of these jobs is really, really rare though.