Staff Analyst (Advanced Analytics, Payments)

Role Overview

Join Airbnb as a Staff Analyst (Advanced Analytics, Payments) (full remote). You will help set the strategic direction for Airbnb’s global Payments operations by turning data into actionable insights, optimizing payment-related user journeys, and collaborating with cross-functional teams.

Key Missions

• Serve as a data thought partner to leadership, providing recommendations that enable integrated, data-informed decision-making.
• Drive Payments roadmaps and user journey optimizations using insights and cross-functional collaboration.
• Design and execute experimentation frameworks, using advanced statistical modeling and causal inference to quantify impact and refine processes.
• Oversee technical details related to fund processing and influence stakeholders across all levels.

Responsibilities / What You’ll Work On

• Translate business questions in Payments into measurable analytics and actionable strategies.
• Apply experimentation and non-experiment causal methods to assess business outcomes.
• Use advanced analytics and data modeling practices to support high-dimensional data and schemas.

Requirements

• 10+ years of industry experience in business analytics with a strong Payments background.
• Expert-level SQL.
• Strong programming skills for analysis in Python or R (at least one required).
• Experience with non-experimental causal inference, experimentation, and machine learning techniques.
• Experience using AI tools to scale workflows and identify opportunities.
• Working knowledge of schema design and high-dimensional data modeling (e.g., ETL frameworks like Airflow).
• Strong storytelling and ability to drive decisions with insights.
• Proven track record working in Payments organizations, including deep technical proficiency across payment areas such as payment processing, risk, and compliance.

Nice to Have

• Master’s or PhD in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
• Experience in a multi-sided platform context.