> Data science for people (Type A), i.e. analytics to support evidence-based decision making
> Data science for software (Type B), for example: recommender systems as we see in Netflix and Spotify
Isn't "type A" business intelligence, and isn't "type B" machine learning? Why doesn't he use those more widely known terms? Or maybe he is referring to something else?
My Job basically aligns with Type A above. I mostly work on optimizing our industrial process through a combination of modelling and simulation work. Other than that I do quality/defect investigations when we have issues with defective batches etc and I do yield optimization work. I also oversee various plant trials as required.
I use Business Intelligence software (like SAS and COGNOS) but I use other tools as well (including my own C/C++ code). I lean heavily on my own theoretical knowledge - in particular metallurgy and minerals processing. (I am a Materials Engineer by qualification). I think most BI people would lack the background theory to do my role.
My Job title was more or less arbitrarily chosen by my manager (Other people in my team have 'Automation Engineer', 'Process Engineer' etc. as their role titles). I consider myself an Engineer above anything else.
The people who do the work you mention (schemas etc) are called Database Admins here. They work for Information Services - different department I'm not all that familiar with.
"Machine learning" includes plenty of activities that can be used to provide evidence for one-off human decision making (e.g., using a model to produce forecasts or to understand sensitivities).