This is very standard in industry (as opposed to academia) and highlights a lot of the reasons why you need ML specialists operating these models, and why you will get garbage in garbage out if you try having non-specialist engineers build, evaluate & operate these types of systems.

For example, in this post the engineer does not adequately handle class imbalance at all, and reaches for a hugely complicated model framework (XGBoost) without even trying something like bias-corrected logistic regression first.

I think this post is just an example of an infra engineer thinking “ML is easy” and when their quick attempt doesn’t work, then just bailing and saying “ML is overhyped and doesn’t work for my problem.”