The vacancy is well-structured with clear expectations and a competitive salary, making it appealing to qualified candidates.
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Overview
Join Airbnb as a Senior Data Scientist in the Payments Data Science organization, focusing on payment strategies and fraud mitigation. Work remotely in the USA with a competitive salary range of $179,000 to $210,000. 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 have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
Responsibilities
- •Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts.
- •Build methods for robust evaluation of ML/AI model efficiency and performance.
- •Identify use-cases for and develop predictive models to classify, segment, and interpret our users’ behavior.
- •Support evaluation and optimization of agentic and LLM-based systems.
- •Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies.
- •Deliver robust research reports and effective data visualizations.
- •Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact.
- •Think strategically about opportunities to improve and scale our brand measurement and customer insights.
Conditions
- •Competitive salary range of $179,000 — $210,000 USD.
- •May include bonus, equity, benefits, and Employee Travel Credits.
- •Remote eligible position with occasional work at an Airbnb office or attendance at offsites.
Requirements
- •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 of experience with a PhD degree.
- •Strong knowledge of causal inference, experimentation, applied statistical modeling, and end-to-end ML development.
- •Skilled in statistical programming (Python or R) and database usage (SQL).
- •Demonstrated track record of owning a business or technical domain end-to-end at a prior company: setting your own roadmap, being the accountable expert others escalate to, and driving a problem to resolution.
- •Proven ability to communicate clearly and effectively to audiences of varying technical levels.
- •Ability to work independently, set your own roadmap, and drive cross-functional alignment.
- •Payments Fraud/Risk Domain expertise 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.