And this is where DS with a deeper more rigorous understanding begin to differentiate themselves by being able to step back and reformulate/re-model the problem

And this is where DS with a deeper more rigorous understanding begin to differentiate themselves by being able to step back and reformulate/re-model the problem into something more like an anomaly detector (in keeping with this example). I can see the argument where ML Engineers and DS w/out a more advanced statistics/STEM background would fail since they would continue down their list of libraries w/in their prescribed toolbox. Granted many problems can be approximated to be good enough, and let's face it, the FAANG/MAANG/whatever companies aren't running things so super critical where a user getting one extra email or ad presentation will cause them serious injury or death. Btw, appreciate your comments.