DoorDash’s new experimentation platform, built on a combination of SQL, Kubernetes, and Python, allows for quick iteration of data-driven feature improvements.
Tag Archives: data science
DoorDash’s ML Platform – The Beginning
DoorDash uses Machine Learning (ML) at various places like inputs to Dasher Assignment Optimization, balancing Supply & Demand, Fraud prediction, Search Ranking, Menu classification, Recommendations etc.
Supercharging DoorDash’s Marketplace Decision-Making with Real-Time Knowledge
DoorDash is a dynamic logistics marketplace that serves three groups of customers:
Merchant partners who prepare food or other deliverables,
Dashers who carry the deliverables to their destinations,
Consumers who savor a freshly prepared meal from a local restaurant or a bag of groceries from their local grocery store.
For such a real-time platform as DoorDash, just-in-time insights from data generated on-the-fly by the participants of the marketplace is inherently useful to making better decisions for all of our customers.
Organizing Machine Learning: Every Flavor Welcome!
DoorDash’s principles and processes for democratizing Machine Learning
Six months ago I joined DoorDash as their first Head of Data Science and Machine Learning.
Personalized Cuisine Filter
The consumer shopping experience is a key focus area at DoorDash.
Analyzing Switchback Experiments by Cluster Robust Standard Error to Prevent False Positive Results
Within the dispatch team of DoorDash, we are making decisions and iterations every day ranging from business strategies, products, machine learning algorithms, to optimizations.