March Madness analytics, AI help data scientist fill bracket

Zach Deane-Mayer, director of data science at DataRobot Inc., has been participating in an annual March Madness pool since he was about 10 years old. It’s a family thing for him. For more than two decades, he’s vied in pools against his father and his brothers, who, as Deane-Mayer puts it, “have traditionally been much better at it.”

However, that underdog status appears to be changing. Over the last few years, Deane-Mayer has been applying machine learning algorithms to March Madness analytics data, giving his picks a boost and himself more of a viable chance in the annual competition. Making brackets with DataRobot Staying loyal to his employer, Deane-Mayer has been creating his algorithms using DataRobot’s automated machine learning tools since starting at the Boston-based startup in 2015.

Author: Mark Labbe

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