Kinds of Data Scientists

I like the distinction, often useful.  But would add a distinction by problem domain, which often adds a further understanding of data types, sources, resources and restrictions that can be essential.  And a knowledge of ethics can also be domain specific.  Good general and non-technical piece ...

The Kinds of Data Scientist   By Yael Garten in the HBR

In 2012, HBR dubbed data scientist “the sexiest job of the 21st century”. It is also, arguably, the vaguest. To hire the right people for the right roles, it’s important to distinguish between different types of data scientist. There are plenty of different distinctions that one can draw, of course, and any attempt to group data scientists into different buckets is by necessity an oversimplification. Nonetheless, I find it helpful to distinguish between the deliverables they create. One type of data scientist creates output for humans to consume, in the form of product and strategy recommendations. They are decision scientists. The other creates output for machines to consume like models, training data, and algorithms. They are modeling scientists.   .... "