Staff Machine Learning Scientist, Applied Causal Inference
DoorDash USA · San Francisco, CA; Sunnyvale, CA; Los Angeles, CA; Seattle, WA; New York City
Don’t apply blind. See how your CV matches this role first — free, in 30 seconds.
You will leave NewLuxJob. We do not receive or handle applications.
- Company
- DoorDash USA
- Location
- San Francisco, CA; Sunnyvale, CA; Los Angeles, CA; Seattle, WA; New York City
- Salary
- $203,500 — $299,300
- Posted
- August 18, 2026
About this job
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. This is not a generic ML role with some experimentation work on the side. 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,…
This is a short summary.
Want to know if you're a fit? Check your CV against this role — free, in 30 seconds.
Similar jobs
See if your CV fits this job
Paste your CV for an instant match score against this role — and get a tailored cover letter in one click.
- Instant match score for this role
- Tailored cover letter in one click
- Free — no credit card