Senior Data Scientist - Payments (Inference)

ABOUT THE ROLE Airbnb’s Payments Data Science organization sits at the intersection of Trust and Payments, powering systems that move money safely and efficiently across the global marketplace. The team focuses on payment optimization for guests and hosts, fraud and risk mitigation, complex measurement, and regulatory compliance. As a Senior Data Scientist – Payments (Inference), you will lead quantitative measurement efforts and bring novel scientific approaches to drive decision making across the platform’s payment experience. WHAT YOU'LL DO You will develop and apply causal inference methods—including experimental, econometric regressions, and quasi‑experimental techniques—to measure a wide range of product and platform impacts. You will build robust evaluation methods for AI/ML models, identify use‑cases for predictive modeling, and support the optimization of agentic and LLM‑based systems. Your work will involve creating new metrics and frameworks that balance competing trade‑offs, conducting deep root‑cause investigations, and measuring long‑term impacts. You will deliver research reports and data visualizations, collaborate with stakeholders, and communicate findings to drive product and business roadmaps. Additionally, you will think strategically about scaling brand measurement and customer insights. WHAT YOU'LL NEED - 5+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (math, economics, statistics, etc.) or 3+ years with a PhD. - Strong expertise in causal inference, experimentation, applied statistical modeling, and end‑to‑end machine learning development. - Proficiency in statistical programming (Python or R) and database usage (SQL). - A proven track record of owning a business or technical domain end‑to‑end, setting roadmaps, and driving problems to resolution. - Excellent communication skills for audiences at varying technical levels. - Ability to work independently, set your own roadmap, and align cross‑functionally. - Payments fraud/risk domain knowledge is a strong plus. - Familiarity with evaluating agentic or LLM‑based systems (e.g., decision‑quality measurement, human‑in‑the‑loop calibration) is a plus. WHY REMOTE This position is US‑remote eligible and supports a fully remote work environment. BENEFITS (If mentioned in the original posting, include applicable benefits such as health plan, parental leave, education stipend, life insurance, equipment stipend, flexible schedule, etc.)