Good data scientist described here seems to have unrealistic expectations at super human level of know-it-all/do-it-all.
I think there are more well-established job architectures like business intelligence analyst, data engineering, user experience designers, product manager, software engineer etc - these roles in combination serve to do a lot of what is described here as data scientist. These roles are easier to hire, have well defined career paths and good ways to get job satisfaction and can scale well as the business-problem-space/orgs grows.
I think the scientist label should be reserved for those who actually do the scientific mathematical research – specialists who have done deep research in specific areas.
For applying pre-existing sciences to solve practical business domain problems, we need lots of engineers, analysts and managers etc who are all trained with AI-first software development practices and just a few specialist data scientists.
I think there are more well-established job architectures like business intelligence analyst, data engineering, user experience designers, product manager, software engineer etc - these roles in combination serve to do a lot of what is described here as data scientist. These roles are easier to hire, have well defined career paths and good ways to get job satisfaction and can scale well as the business-problem-space/orgs grows.
I think the scientist label should be reserved for those who actually do the scientific mathematical research – specialists who have done deep research in specific areas.
For applying pre-existing sciences to solve practical business domain problems, we need lots of engineers, analysts and managers etc who are all trained with AI-first software development practices and just a few specialist data scientists.