> Data science & engineering should be treated as a single collection of skill-sets. This can be tough because there could be a lot in that skill set. You can'

> Data science & engineering should be treated as a single collection of skill-sets. This can be tough because there could be a lot in that skill set. You can't realistically expect someone to have solid knowledge of statistics including specialising in the sub-field and type of algorithms that your product needs, and also be able to write good code and act as a developer, and also have solid knowledge of all the tools for data streaming/processing/ETL. There is a point at which you're just stretching yourself too thin if you try to do all of these at once. Of course, stuff like knowing how to interact with a database or employing good software development practices should be a very basic prerequisite and some scientists certainly shift things too far in the other direction and use their academic knowledge as an excuse to write poor code and not learn new tools. I guess what I'm trying to say is that they are distinct skills but you still need all of them to some extent and striking the correct balance in one's skillset is really difficult.