I was about to comment about how terrible this entire thing is, but then saw that literally every comment here is a negative take on the article. It would be n

I was about to comment about how terrible this entire thing is, but then saw that literally every comment here is a negative take on the article. It would be nice if someone said something at least semi-positive, so here's my attempt! I think, although it misses the mark, something like this is really needed. I've worked in the data science field for about 5 years now, and see the same problems at every organisation to varying degrees: - data scientists struggle to balance long term research efforts with immediate value propositions - communicating the business value of data science tasks (such as forecasting) seems to often struggle between being rigorous, and understandable to non-data-scientists - its hard to build data science teams with both good statistical foundations and good software engineering practices, and both of these are table stakes for delivery of anything meaningful. I think as an industry, data science is getting there slowly. Part of the problem is that tools are touted as the answer much more that practice. So, although I don't agree with all the sentiments here, I think we need more thought, like this, on the principles behind success for data teams.