Lead Analyst of Advanced Analytics

Join Airbnb as the Payments Insights Analytics Lead, where you will play a critical role in executing the strategic direction of our Payments operations. You will enable data-driven decision making across various organizations, collaborate on financial risk management, and optimize the end-to-end payments journey. Your expertise in business analytics, SQL, and programming languages will be essential in driving measurable impact and influencing strategy.

• Lead the execution of the strategic direction of Airbnb's Payments operations by enabling data-driven decision making across the Payments Platform.
• Collaborate with cross-functional teams to drive process improvements and streamline payments data globally, while building relationships with stakeholders at all levels.
• Utilize advanced data analytics, AI/ML techniques to inform strategic decision-making and assist with building new payment strategies.
• Working knowledge of schema design and high-dimensional data modeling (ETL framework like Airflow)
• 8+ years of industry experience in business analytics and a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research)
• Ability to work under conditions of ambiguity in a fast-growth, sometimes uncertain and complex environment - comfortable acting with minimal planning, direction, and supervision. You can identify issues both within and outside of your immediate scope, and propose solutions
• Expert skills in SQL and expert in at least one programming language for data analysis (Python or R)
• Exceptional communication and storytelling skills, you can distill highly technical work (model outputs, experimental results, complex data analyses) into clear, actionable insights for senior leadership and business stakeholders
• Have experience supporting Payments teams and/or have worked closely with payments organizations, with demonstrated exposure to multiple payment risk domains such as trust & safety, identity verification, fraud prevention, chargebacks, regulatory compliance, and financial risk management
• Experience with non-experimental causal inference methods, experimentation and machine learning techniques, ideally in a multi-sided platform setting