Are you a data scientist or a decision scientist? Interesting question recently raised by Deepinder Dhingra, head of products and strategy at Mu Sigma in his article ‘Data science’ misses half the equation: an argument for ‘decision s...
Of course data science needs to be useful. We are not simply trying to find patterns in data, we are trying to find useful patterns in data. But the point is well taken that the business need and the business context need to be top of mind.
Another way to look at this is through the findings of Harris, Murphy, and Vaisman published in their 2013 study “Analyzing the Analyzers” which we reviewed in How to Become a Data Scientist. Harris et al make the point that their research reveals four distinctive types of data scientists:
All of these are necessary, but only the group identifying and Data Businesspeople show a depth of understanding of how the business model and business needs relate to the problem at hand. This is part of the famous T-shaped profile we are now all so familiar with.
Data Businesspeople, or Decision Scientists then are most likely to be the senior DS on the job who has the initial role of defining the business problem as well as the final role of explaining the solution.
All the same, it would be good to have a sign hanging over our bathroom mirror that we would see each morning reminding us that being a Decision Scientist is what our employers want even if just being a Data Scientist is what we love.
About the author: Bill Vorhies is President & Chief Data Scientist at Data-Magnum and has practiced as a data scientist and commercial predictive modeler since 2001. Bill is also Editorial Director for Data Science Central. He can be reached at: