Lead, Advanced Analytics, Fraud and Safety Operations

Join Airbnb as a Lead in Advanced Analytics to mitigate fraud and safety risks through data-driven insights and innovative solutions. Collaborate with cross-functional teams to enhance decision-making processes. 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.

• •Build self-service data tools that empower non-technical teams to ask deep questions, run “what if” analyses, and generate actionable, data-backed outcomes without gatekeeping.
• •Craft compelling narratives and dashboards that surface insights to executives and cross-functional teams.
• •Ensure fraud and safety metrics are future-proof, scalable and supported by clear governance, ownership and automated monitoring.
• •Own launch and decision criteria for fraud and safety experiments by defining launch thresholds, gating metric releases on decision quality, and helping leadership make data-driven decisions.
• •Support external audits, law-enforcement requests, and board-level reporting with rigorous, well-governed data and clear analytical narratives.
• •Operationalize frameworks that instantly assess and size the platform, reputational and regulatory impact of fraud incidents, enabling rapid escalation, crystal-clear retrospectives and systematic learning.

• •Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands.
• •The base pay range is subject to change and may be modified in the future.
• •This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
• •Pay Range $164,000 — $191,000 USD.

• •5+ years of experience in data analytics, fraud, safety, or a related quantitative domain, with deep individual-contributor expertise, or 2+ years of industry experience with a PhD.
• •Proven ownership of large-scale data products or taxonomies.
• •Strong SQL and data-modeling expertise; familiarity with Python/R; working knowledge of ML pipelines.
• •Strong experience designing experiments and applying causal inference methods, ideally in a multi-sided platform setting.
• •Deep understanding of how to measure rare events with statistical rigor, including prevalence estimation, sampling strategy, and statistical power.
• •Familiarity with account integrity, user authentication and connected-account vectors, such as social logins, device fingerprinting and related identity signals.
• •Skilled in incident impact scoping, post-incident analytics, scenario planning or tabletop exercises, and translating insights into systematic improvements.
• •Track record of enabling legal, policy, ops, product, and engineering teams to make independent, forward-facing, data-driven decisions via self-service tools.
• •Exceptional storyteller with the ability to make complex analytics actionable for every audience.