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Learn how DoorDash solves the dispatch problem using ML and optimization

If you are interested in industry data science applications that combine machine learning, optimization, experimentation, and simulation, then you will enjoy this new article I wrote on the DoorDash engineering blog “Using ML and Optimization to Solve DoorDash’s Dispatch Problem.” The article takes a deep dive under the hood of DoorDash’s logistics platform. We discuss the unique factors we have to consider in our dispatch problem and how we optimize over a variety of data inputs, including predictions from our ML models, to ensure speedy deliveries and maximize opportunities for Dashers. Check it out: Using ML and Optimization to Solve DoorDash’s Dispatch Problem