Creating a Consistent Interview: Dealing with Bias & Noise at an Institutional Level
1:30 - 2:00 | Thursday, May 23
Few decisions on a data science team impact its future as much as hiring. While we all know about the importance of managing and combating unconscious bias in our interviews, at Wayfair we also worry about tackling the noise. In this talk Patrick will cover what we mean by noise in the interviewing process, as well as updates on efforts at Wayfair to handle noisy decision making as they grew to an organization with over a hundred data scientists and onwards to their next hundred.
Associate Director, Data Science Measurement and Attribution, Wayfair
Patrick is Associate Director for Measurement and Attribution as part of Wayfair’s data science team. Patrick leads teams that drive to measure the impact of everything Wayfair does, from rolling out new models to entering new categories of business as well as drive Wayfair’s multi-touch attribution model which learns the value of each touchpoint in a customer’s journey to purchase and retention. Patrick is passionate about allowing data science to directly drive business value and democratizing the tooling around data science into the hands of everyone in a corporation. Previously, Patrick founded and lead monetization data science at Pinterest where he also developed and ran the Pinterest data science course across sales, engineering, and analytics, and was the head of data science at Yelp.
Patrick holds a Ph.D. from Case Western Reserve University in experimental particle astro-physics where he worked on an experiment a mile underground in a gold mine in South Dakota. In his spare time he enjoys running, biking, and surfing.