# Senior Data Scientist - Payments (Inference) at Airbnb

- Company: Airbnb
- What the company does: Get an Airbnb for every kind of trip → 8 million vacation rentals → 2 million Guest Favorites → 220+ countries and regions worldwide. Backed by General Catalyst, Greylock and Kleiner Perkins.
- Company website: http://www.airbnb.com/
- Type: Startups (AI role)
- Level: Senior
- Location: Remote - USA
- Work setup: Remote
- Posted: 2026-08-14
- Apply by: 2026-10-12
- Apply: https://careers.airbnb.com/positions/8123037?gh_jid=8123037
- Page: https://www.1752.vc/careers/jobs/airbnb-senior-data-scientist-payments-inference/

## About the role

You will join the Payments Data Science organization, which sits at the intersection of Trust and Payments and powers the systems that move money safely and efficiently across Airbnb's global marketplace. The team spans payment optimization for guests and hosts, fraud and risk mitigation, complex measurement, and regulatory compliance. We partner directly with Payments product and engineering leadership, Finance, and Trust to ensure every transaction is fast, safe, and compliant at global scale.

## What they're looking for

- Inference: Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts
- Optimization: Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies
- Communication: Deliver robust research reports and effective data visualizations. Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact
- Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights
- 5+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (math / economics / statistics, and etc.), or 3+ years of experience with a Phd degree
- Strong knowledge of causal inference, experimentation, applied statistical modeling, and end-to-end ML development

Tags: Data Science