[dvcat]

2) "Publishing" (Blogging about this) will help. I am not too sure what you mean by "know the techniques well enough". In my case, I cracked a few books on LA/Stat and worked through them and encountered situations where I had to use those skills repeatedly as part of courses I had taken in School. Doing tiny projects where you are able to acquire mathematical intuition for certain concepts will be useful.

4) So the fact of the matter is that you should be versatile enough to absorb their tech stack as soon as possible. That is possible only if you have worked in depth in at least one tech stack. This is especially true for Map Reduce based technologies.

Its hard to be specific: All those things are doing in analytics departments. There are not many machine learning people in my place of work so I mostly find problems that require algorithmic solutions and try to see if I can solve them. Things probably are more structured in larger companies..