Because when we sit down and think about a problem, when we take the time to not only understand what our feature space “is” and what it “implies” in the real-world — then we are acting like machine learning scientists. Otherwise, we [are] just a bunch of machine learning engineers, blindly performing black box learning and operating a set of R, MATLAB, and Python libraries.
The takeaway is this: machine learning isn’t a tool. It’s a methodology with a rational thought process that is entirely dependent on the problem we are trying to solve.
Get off the deep learning bandwagon and get some perspective – PyImageSearch
Kenkyuu 
Thanks for the quote! 🙂
Indeed the difference between data scientist and engineer is more than trivial – as the space develops, being a data scientist is what will benefit businesses most. On the other hand becoming an expert in the technology is not sought after, long term – many doing R and Python were C++ specialists before but the useful ones were all about problem solving and thinking. 7 years time, it’ll change again, but problem solvers will still rule.