The Data Science Bubble

Data science has produced some of the greatest tech innovations in the past decade, but as practiced in many organizations it’s also completely unsustainable. Producing more relevant models, mitigating risk and keeping up with the pace of the field will require organizations to rethink how they do data science.

The author is Principal Data Scientist @ Aetna, and this post contains his thinking on how data science projects should be chosen, run, and funded. Excellent read. 

The one thing I'd add is that some organizations already understand how to run speculative projects like this: most R&D spend is high-risk. I think the problem is that many managers and organizations who have little history with making decisions around high-risk projects are now doing so.


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