Back

Speaker "Chris Robison" Details Back

 

Topic

Data Science and Enterprise Engineering

Abstract

How Data Scientists and Engineers work in tandem to achieve real-time personalization at Overstock Personalizing online experiences for users is nothing new, but real-time personalization requires sub-second speed and close collaboration between data scientists and enterprise engineers. Like the hands on a clock, data scientists and enterprise engineers have shifted their focus from hour- hand quickness to minute-hand speeds with a craving to take advantage of each tick of the second hand and personalize in real-time. Previously, daily activities were consumed on improving customers’ experiences tomorrow. Workflows ran overnight when on perm resources were not being tasked. The focus was on the-day-before jobs, always inching forward 24-hours behind. Since then, we have shifted to hourly jobs and even to tasks that run every five minutes. Finally, we have been personalizing user experiences within the same day and even during the same session. But could we personalize these experiences instantly, immediately, and in real-time? What would that require? What does it look like? Michael Finger and Chris Robinson explore how data scientists and engineers are working in tandem to achieve real-time personalization at Overstock.com

Profile

Chris Robison serves as the Data and Audience Lead for Digital Marketing at Overstock, where he and his team utilize big data and machine learning to create personalized shopping experiences for customers. He works extensively on cross-channel marketing leveraging modeling techniques from classical time series to cutting-edge Artificial Intelligence. Prior to joining Overstock in 2016, Chris gained widespread experience at early-stage startups using Spark and building out data science frameworks and solutions. He graduated from the University of Utah with dual Masters Degrees in Computer Science and Statistics.