There is always some exception to the rule. Frankly the issue is more the number of topics one needs to learn to actually add value as a data-scientist. Junior data scientists need a hell lot of supervision compared to analysts or data-engineers. Most of what it takes to be a data-scientist is acquired on the job rather than something learned in class. And yes some of that could be checked during the interview, but that would also mean a very low pass rate and a lot of time spent hiring on these roles. I would rather hire these people straight out of college in role where they would have much more chance to excel, and would need less supervision. If they are good enough then give them more modeling tasks.