It's a price data scientists have to pay in order to work in rapidly evolving business and solution spaces. Someone within the local organization has to experience all these tools before being able to reach similar conclusions. Many organizations are still struggling to get the data science infrastructure in place so they look for full-stack people to help get the ball rolling and start making progress on some initial set of prioritized business problems.

A few organizations are further along on that journey enabling their data scientists to focus on things other than process and tooling. Full-stack will be in demand until the solution space stabilizes and the bulk of organizations catch up.