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AirbnbAirbnbUnited States

Senior Manager, Advanced Analytics, Fraud & Safety Operations

Leads a team of advanced analysts to build self-service analytics systems and data products for fraud detection, safety measurement, and privacy risk management at Airbnb. Requires 8+ years in analytics/risk, strong SQL/Python/ML skills, and experience owning large-scale data taxonomies.

212k – 265k
Remote8+ YOEData Analytics

About the role

Responsibilities

  • Own end-to-end analytical workflows for platform safety controls: data ingestion, feature engineering, modeling, experimentation, and visualization.
  • Co-own and drive the enterprise-wide “Safety Single Source of Truth” (SSoT) strategy—a unified, structured data asset and taxonomy that underpins decision-making across Product, Operations, Policy, and Legal. Ensure metrics are future-proof, privacy-compliant, and globally scalable.
  • Build self-service data tools that empower non-technical teams to ask deep questions, run “what if” analyses, and generate actionable, data-backed outcomes.
  • Craft compelling narratives and dashboards that surface insights to executives and cross-functional teams.
  • Lead incident “war rooms,” presenting fast, actionable insights during high-severity events.
  • Contribute to policy design (e.g., connected-accounts enforcement thresholds).
  • Support external audits, law-enforcement requests, and board-level reporting.
  • Partner with Policy, Product, Engineering, Fraud and Safety Ops, and Legal to align analytics with global safety and privacy regulations (e.g., GDPR, CCPA).
  • Operationalize frameworks that instantly assess and size the platform, reputational, and regulatory impact of safety incidents.

Requirements

  • 8+ years of experience in analytics, risk, or safety; 3+ years leading high-performing teams.
  • Proven ownership of large-scale data products or taxonomies in a regulated environment.
  • Strong SQL & data-modeling expertise; experimentation design, familiarity with Python/R; working knowledge of ML pipelines.
  • Deep understanding of measuring rare platform events with statistical rigor, user authentication & connected-account vectors (e.g., social logins, device fingerprinting), circumvention tactics (e.g., multi-accounting, listing duplication, payment abuse), global privacy and data-protection standards (GDPR, CCPA, SOC 2).
  • Skilled in incident impact scoping, post-incident analytics, and scenario planning or tabletop exercises.
  • Track record of enabling legal, policy, ops, product, and engineering teams to make independent, data-driven decisions via self-service.
  • Exceptional storyteller with a flair for making complex analytics actionable.

Nice-to-Haves

  • Prior work in marketplace, fintech, or travel/hospitality tech environments.
  • Familiarity with real-time decision engines, graph analytics, and anomaly-detection frameworks.
  • Experience leading hybrid teams (onsite/remote) and managing third-party analytics vendors.
  • Statistics or quantitative graduate degree (MS/PhD).

Skills

SQLPythonRMl PipelinesData ModelingExperimentation DesignStatistical AnalysisPython/RGraph AnalyticsAnomaly Detection

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