We increasingly expect the world around us to be “smart” and seamlessly adapt to our taste and habits. Building this world is a difficult task — and it requires new ways of thinking about data. We’ll talk about what it takes to build data products — from analytics, exploration and technical challenges to the role of user feedback and machine learning.
Monica is a data scientist with a passion for turning data into products, actionable insights, and meaningful stories. As the VP of Data for Jawbone, she focuses on developing data-driven products that promote a healthier lifestyle and on finding stories in the UP wristband data. Prior to Jawbone, Monica was one of the early members of the LinkedIn data science team, where she developed and improved some of LinkedIn’s key data products for matching jobs to passive candidates, discovering people you may know, and recommending groups you may like. Monica’s compelling data stories are often picked up by the mainstream press, including the Wall Street Journal, The Economist, NPR and CNN. Monica holds a Ph.D. in Computer Science from CMU, where she focused on text mining and applied machine learning. She authored eight US patents and numerous papers that appeared in top-tier peer-reviewed journals and conference proceedings.