This is a byproduct of hiring bootcamp grads or tasking a modeling project to engineers who read some tutorials. People think they can scan a few Jupyter notebooks and then professionally solve statistics problems.

People wonder why it’s hard and expensive to hire ML engineers... because they actually solve these problems with craft. Meaning, they systematically grow understanding of the data, start with simple models, and have well articulated reasons explaining cases when complexity is justified.

It's the machine learning version of people who use hadoop if they could have used command-line utilities.