I recently became a data scientist and was lucky enough to find a role where my company is willing to train & mentor me for the role. The large volume of applicants may be more due to the ambiguity of what is required to be good at the role. Companies put out a wide variety of messages around what they want: PhD converts, experienced developers, advanced business analysts. I think the ambiguity coupled with the hype drives up applicants that are misaligned with the company's goal (if they even have a tangible goal).
again - strongly agree with this. Its absolutely right that the company should put time and effort into training and mentoring you because its very unrealistic to expect someone who has the potential to be a strong data scientist to have all the skills for that particular company on day 0
One valuable aspect of mentoring is the transference of institutional knowledge to new people. Technical skills are important, but learning about internal projects, past history/lessons, philosophy, etc are fairly critical for an organization to stay alive and survive through tough times.
Places I've seen that have zero mentoring also have zero transfer of institutional knowledge outside of osmosis and hubris (we train our people during our once a year 3 day meeting!). The end result is a few events can have a major effect. One senior person leaves and suddenly entire projects and systems are derailed and backlogged because no amount of technical skill can replace the knowledge of what actually went on in those products/projects in the first place.
