Back in 2015 I did a webinar session for CIOs titled Data Science: Trenches to the Boardroom (10 Lessons) The definition I was using at the time was: Mul

Back in 2015 I did a webinar session for CIOs titled Data Science: Trenches to the Boardroom (10 Lessons) The definition I was using at the time was: Multi-disciplinary knowledge, methods and skills for building systems that acquire, manage and analyze data to deliver insight and automate quantitative analyses like segmentation, classification and prediction in support of real-time business processes. I focused on the building of systems that automate analysis. I did this in an effort to distinguish what I am now doing from my previous work as a "research-based consultant." In that role I would take on a business problem/question and use a variety of qualitative and quantitative techniques to investigate and come to an evidence based recommendation for the client. But now, I build systems that often automate away the work of an entry level analyst. Or, use the models to drive systems that automatically adjust prices to changes in the competitive landscape on a SKU by SKU basis. Or, build systems that create added-value data sets that are in turn sold to another company.