Another interesting aspect here are "Data Science" programs in colleges/universities. My experience looking at new grads is they are all focused on statistical and computational modeling/algos, albeit with a lot of variability in the depth of their education (e.g. apply a linear model in SAS vs specify a new covariance structure to the errors and derive the respective equations or code a linear model with this).
This has created a situation where lots of people want to get into a specific Data niche and they see Data Science as one thing. But how many Data Modeling jobs are there and how many can there be? Especially when you consider how quickly statistical and machine learning is being automated and is built into software.
Any company working in Data does lots of stuff outside of this. This includes BI, Data Integration, DB Modeling, Custom Visualizations (e.g. D3), Security, Customization, and sitting in front of clients to scope projects and explain how to get value from their Data.
We have a person who is amazing at getting customer authentication integrated into our Data product. So when a customer asks "We use a token and blah blah blah for our data security" this person figures out how to get our software to authenticate through their system. This person is a great R programmer, but they know the bare minimum about modeling in R.
If our statistical model is half-baked that might jeopardize a deal. But If we can't use their security and authentication infrastructure the deal is dead - no compromise there. So this person is really critical in our data team, but they aren't what a lot of people see as critical to Data Science.
The growth of Data jobs is going to be huge if we do not only include the jobs which require R modeling (or related) skills. A lot of people are going to need to let go of "I learned statistics so the only job I want to do is statistical modeling" to get jobs in this industry.
