[PaulHoule]

I talk a lot of people who've had trouble with "data scientists" who are strong in statistics and know some matlab or R or something like that, but know nothing about the craftsmanship of programming.

By that I mean skills like using version control, writing software that is maintainable, working with a team that uses project management software, things like that.

A common kind of workflow is that a data scientist develops an algorithm and makes tweaks to it, and that this gets baked into a production system.

If the data scientist throws something over the wall and it takes the developers a few weeks to get it ready for real use, the "real time" productivity of the team is going to be awful. The closer we come to the data scientist checking the changes in and that's that, the more valuable the data scientist is.

[jebus989]

This is absolutely a fair comment, coders but not software engineers, and is the same problem that's permeated bioinformatics for the last decade or so. (As an aside, it's fun hearing grand claims about data science revolutionising medicine in 10 years [0], when the same claims were made about bioinformatics 10 years ago.)

[0] https://twitter.com/HanChenNZ/status/473825783874859008