Industry Session 2: Offbeat

Date: Thursday, Oct 9, 10:30-12:00


Virtual Personal Shopping Assistants

by Manu Sharma (Shopkick)

Shopkick is the most widely used physical world shopping app. With over 8MM users and 200+ retail and brand partners, shopkick helps shoppers make better shopping decisions by providing personalized deals and content as well as rewarding users for simply visiting stores. Come to this session and find out how we are using data and algorithms to create a unique real world, location aware, personalized recommender system to bridge the online / offline gap by putting a digital overlay in the physical world.

Dr. Manu Sharma is VP of growth and Data Science at shopkick. His main interests are in the fields of user behavior, viral growth, predictive modeling, recommendation engines, collaborative filtering, and drawing compelling and fun insights from data. Prior to joining shopkick, he was Director of data science at LinkedIn where he ran a team of ~30 Data scientists focused on solving a wide variety of problems for LinkedIn and beyond. As Lead Research and Development Scientist at Cake Financial, a consumer internet startup for retail investors, he designed and implemented a portfolio recommender system and a Stock / Fund rating system. He has co-authored 6 patents, and several research papers. He holds a PhD in Chemical Physics from Princeton University and a MSc in Chemistry from the Indian Institute of Technology, New Delhi.

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