What major differences are there between the new data science careers and what developer's have been doing in university research departments for years now? Is

What major differences are there between the new data science careers and what developer's have been doing in university research departments for years now? Is it simply a matter of scope? Transitioning from relatively small clinical trial sets to marketing data. Is credentialing needed because there is greater responsibility to formulate mathematical models in this path? If so how is that different than creating domain specific algorithms... Basically I'm trying to understand why this is seen as a unique career path as opposed to just another pivot developers may have to adapt to if they want to stay relevant or be on the cutting edge.