I meant "develop" in the software sense. Data scientists use off-the-shelf libraries during initial research, but those libraries usually lack an important feature preventing them from going into production (typically, no support for concurrency).

I am sure it takes much less than "years" ... to learn most of data analysis tricks.

I used to be cynical about "data science," too. After four months of working on a data science team, though, I'm a believer.

A data scientist is really a "full-stack data developer." He or she needs the ability to work with advanced models, use them to analyze large amounts of data, and modify those models to work concurrently or in a distributed system if desired (and its often desired). It's more than just "analysis tricks."