Improving Online Experiment Capacity by 4X with Parallelization and Increased Sensitivity
Originally posted here by Doordash. Data-driven companies measure real customer reactions to determine the efficacy of new product features, but the inability to run these experiments simultaneously and on mutually exclusive groups significantly slows down development. At DoorDash we utilize data generated from user-based experiments to... Read more
Solving for Unobserved Data in a Regression Model Using a Simple Data Adjustment
Article originally posted here by Doordash. Making accurate predictions when historical information isn’t fully observable is a central problem in delivery logistics. At DoorDash, we face this problem in the matching between delivery drivers on our platform, who we call Dashers, and orders in real-time. The... Read more