Hiring for a “data scientist” when you need a quantitative researcher or machine learning specialist is akin to hiring for a “doctor” when you could mean a neurologist, pediatrician, or anaesthetist. As the breadth and depth of the data science field has matured, roles have become more specialized and sophisticated.
No clear sense of the skills required to satisfy an organization’s data science needs. This results in vague job descriptions that fail to attract the right candidates, and excessive time spent evaluating applicants. It can also lead to new hires having the wrong expectations for their roles, and company-wide inefficiencies due to the wrong talent being in the wrong place.