At DoorDash, getting forecasting right is critical to the success of our logistics-driven business, but historical data alone isn’t enough to predict future demand.
Category Archives: AI & ML
How to Drive Effective Data Science Communication with Cross-Functional Teams
Analytics teams focused on detecting meaningful business insights may overlook the need to effectively communicate those insights to their cross-functional partners who can use those recommendations to improve the business.
Running Experiments with Google Adwords for Campaign Optimization
Running experiments on marketing channels involves many challenges, yet at DoorDash, we found a number of ways to optimize our marketing with rigorous testing on our digital ad platforms.
Building Flexible Ensemble ML Models with a Computational Graph
DoorDash extended its machine learning platform to support ensemble models.
Wanted: Data Scientists with Technical Brilliance AND Business Sense
DoorDash seeks data scientists who prioritize the business impacts of their work.
2020 Hindsight: Building Reliability and Innovating at DoorDash
DoorDash recaps a number of its engineering highlights from 2020, including its microservices architecture, data platform, and new frontend development.
Things Not Strings: Understanding Search Intent with Better Recall
For every growing company using an out-of-the-box search solution there comes a point when the corpus and query volume get so big that developing a system to understand user search intent is needed to consistently show relevant results.
We ran into a similar problem at DoorDash where, after we set up a basic “out-of-the-box” search engine, the team focused largely on reliability.
Iterating Real-time Assignment Algorithms Through Experimentation
DoorDash operates a large, active on-demand logistics system facilitating food deliveries in over 4,000 cities.
Building a Gigascale ML Feature Store with Redis, Binary Serialization, String Hashing, and Compression
When a company with millions of consumers such as DoorDash builds machine learning (ML) models, the amount of feature data can grow to billions of records with millions actively retrieved during model inference under low latency constraints.
Uncovering Online Delivery Menu Best Practices with Machine Learning
Restaurants on busy thoroughfares can use many elements to catch a customer’s eye, but online ordering experiences mostly rely on the menu to generate sales.