Staff Machine Learning Engineer, Causal Inference
DoorDash · San Francisco, CA; Sunnyvale, CA; Los Angeles, CA; Seattle, WA; New York City, NY
About this role
About the Team
DoorDash is building the next generation of causal decisioning systems for New Verticals: grocery, convenience, retail, alcohol, pets, flowers, and other emerging categories. These businesses operate in high-dimensional, messy marketplaces where every consumer, merchant, item, promotion, substitution, search result, and delivery promise creates a causal question.
About the Role
We are hiring a Causal Machine Learning Engineer to help build the causal ML foundation behind how DoorDash grows New Verticals. We are looking for someone who has built or deeply worked on production causal systems: uplift models, heterogeneous treatment effect models, surrogate metrics, experimentation platforms, counterfactual policy evaluation, promotion optimization, or marketplace decisioning systems.
You will join a small, senior pod of causal ML and econometrics experts working across ML, Analytics, Product, and Engineering. The mandate is to build the causal spine for a large-scale consumer marketplace.
You're excited about this opportunity because you will…
Design, build, and productionize causal ML systems that influence real marketplace decisions across New Verticals.…
Summary from DoorDash's official Greenhouse career feed — read the full description on the original posting ↗
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