Its quite hard to see the full picture of how these statistical models work without experience across a hard science, stats and AI itself. However, people with backgrounds in mathematical finance would also have enough context. But its seemingly rare in physics, csci, stats, ai, etc. fields alone.
I'd hope that most practitioners in applied statistics could separate properties of the data generating process from properties of its measures; but that hope is fading the more direct experience I have of the field of statistics. I had thought that, at least within the field, you wouldn't have the sort of pseudoscientific thinking that goes along with associative modelling. I think mathematical finance is probably the only area where you can reliably get an end-to-end picture on reality-to-stats models.