What does it really take to build a data product? Recall and relevancy are only parts of the challenge. In fact, an entire new approach is required to build consistently great data products. This includes new paradigms of design, web development, engineering, and testing that allow a team to prototype for 1x, build for 10x, and engineer for 100x. I’ll explain the Data Jujitsu approach which is an agile approach that supports all these scales.
DJ is the “Data Scientist in Residence” at Greylock Partners.
Previously he was the Chief Product Officer for Color and the Chief Scientist at the LinkedIn Corporation, leading the Analytics and Data Teams. Some of the products shipped include, People You May Know, Who’s Viewed My Profile, Talent Match, Skills, and Career Explorer.
He has held roles at Skype, PayPal, and eBay. As was a member of the faculty at the University of Maryland, he helped start a major research initiative on numerical weather prediction. As an AAAS Science & Technology Policy Fellow for the Department of Defense, Dr. Patil directed new efforts to leverage social network analysis and the melding of computational and social sciences to anticipate emerging threats to the US. He has also co-chaired a major review of US efforts to prevent bioweapons proliferation in Central Asia and co-founded the Iraqi Virtual Science Library (IVSL).
More details can be found on his LinkedIn profile.
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