Data Science Leaders: There are too many of you

Ask anyone at the summit and they’d probably tell you that if you think the talent shortage is bad, the leadership talent shortage in data science is far, far worse.Most data science leaders today are what I like to call “transcended data scientists.” People who pursued formal training in science, engineering, or statistics and then, by some miracle, woke up one day to realize that they were more interested in making data useful than chasing mathematical complexity for its own sake.Data science leaders exist against all odds.Data science leaders: There are too many of you because you exist against all odds..We can’t expect data scientists to transcend and instantly know how to be good leaders and decision-makers..Employers, how do you know if you’re hiring the real deal to lead your data team?.To make sure data science is not a bubble, we urgently need specialized leadership..Somehow, good data science leaders do exist and the skills are there..For the past few years, I’ve been working hard within Google to grow a new breed of thinker, positioned to lead or work effectively as part of a team focused on the application of data science to real problems..To build the right skills, we took ideas from data science and engineering and augmented them with the behavioral and managerial sciences..That’s why we started calling it decision intelligence engineering (though you can think of it as applied data science++ if you prefer).Let’s train a new breed of thinker: the decision-maker who has the skills to make data science teams successful.I’ve always believed that data science is a team sport that benefits from skills diversity, so I designed our training program to encourage participation from, and be accessible to, humans of all backgrounds..I hope that reading this inspires at least a few of those who know the data science decision-maker’s craft to join me in recognizing it as a discipline in its own right and sharing our wisdom as widely as possible.. More details

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