Staff Data Scientist, Long-Term Impact — Airbnb (Remote US) — Causal Inference at Scale
The Community You'll Join
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home — and has since grown to over 5 million hosts who've welcomed more than 2 billion guest arrivals in almost every country on the globe. The Core Data Science team ensures we're leveraging state-of-the-art science for the highest possible impact on the business and community, building reusable tools and models that empower DS teams across the organization.
The Difference You'll Make
Estimating the causal impact of product changes is core to data science at Airbnb — typically through short-term experiments or quasi-experiments. But what we ultimately care about is long-term impact. This role is about building frameworks that connect short-term outcomes to long-term impact: developing and improving our long-term impact estimation frameworks and owning the most important estimation problems you identify.
Success means better long-term impact estimation in practice — not just in theory.
A Typical Day
- Develop causal estimates for the long-term impact of short-term metric movements
- Build and refine frameworks that link experiment outcomes to durable business value
- Own high-stakes estimation problems end to end, fitted to Airbnb's problem space and stakeholder needs
- Partner with product, engineering, and DS teams to make the science actionable
Who You Are
A senior data scientist with deep causal inference experience — experimentation, quasi-experiments, and long-term measurement. You can develop the science AND make it practical for stakeholders. This is a remote role based in the USA.
If you love hard measurement problems with real-world impact, apply directly below.
🚀 Ready to Apply?
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