Advanced Analyst

About Airbnb

Airbnb was born in 2007, connecting Hosts with guests worldwide. Today, over 4 million Hosts welcome billions of guest arrivals across 220+ countries, fostering authentic, connected experiences. At its core, Airbnb thrives on a creative spirit, curiosity, and imagination, constantly seeking unconventional solutions. The company's community is built on connection and belonging, driven by a commitment to all stakeholders and a unified team dedicated to leading as a 21st-century enterprise.

The Team

We are seeking a data scientist/Advanced Analyst to join the Fraud & Safety Organization (FSO). This role supports Product, Operations, and Policy leaders by driving data-informed decision-making to protect trust across the platform. The FSO Advanced Analytics team integrates measurement, experimentation, and insights into product defenses and user journeys. You will collaborate with product managers, engineers, data scientists, and operations teams to design scalable systems that detect and mitigate fraud across various domains. This includes shaping trusted user journeys, building compelling data narratives, and strengthening measurement and experimentation practices using Airbnb’s extensive data and ML infrastructure.

The Fraud & Safety Operations Analytics team specifically seeks an operations data analyst with a proven track record of leveraging diverse data sources. This role involves identifying, analyzing, visualizing, and interpreting trends to resolve high-priority business problems. You will support the Fraud & Safety Investigation operations team, driving impactful results for Airbnb, and will be involved in the end-to-end project lifecycle, from problem definition to creating dashboards for sharing insights.

What You Will Do

• Enable faster turnaround on operational metrics, reporting, and experiment readouts.
• Strengthen detection, review efficiency, and enforcement visibility.
• Support high-priority fraud and abuse operations analytics with immediate execution bandwidth.
• Partner with Operations, Product, and Data Science teams to translate findings into actionable strategies.
• Understand where system leakages occur (Entry → Detection → Review → Enforcement → Appeal analysis).
• Ensure the support organization operates effectively at scale.
• Connect operational actions to risk outcomes, including Fraud Loss and Risk Monitoring.
• Validate effectiveness through experimentation and initiative measurement.
• Maintain governance and metric hygiene: define, create, and visualize metrics/dashboards for problem definition and tracking project success/workstream health.
• Build strong relationships and trust with stakeholders, ensuring their continuous engagement in projects.

Requirements

• 5+ years of experience in an operations data analyst or similar role within a high-throughput organization.
• High proficiency in Advanced SQL for developing complex queries.
• Experience building full workflow/funnel metric suites (experience in Customer Support/Operations is a significant plus).
• Working knowledge and understanding of Forecasting techniques, Experiments, Causation & Correlation, and Statistical models.
• Experience with Superset, Tableau, or similar Business Intelligence (BI) platforms (e.g., Salesforce) to develop reports and dashboards.
• Ability to work independently with stakeholders, write detailed requirements, and solve analytical problems in fast-paced, ambiguous environments.
• Capable of serving as a liaison between business and technical teams (e.g., AE/DE, Engineering) to drive effective, timely solutions, translating insights into actions that fulfill both strategic and operational needs.
• Ability to team effectively with others and build relationships at all levels, both within the immediate team and with broader stakeholders.

Highly Preferred

• Experience in Operations or Customer Support team analytics.
• Undergraduate degree or higher in a quantitative field.

Key skills/competency

• Advanced SQL
• Data Analysis
• Fraud Detection
• Risk Mitigation
• Experimentation Design
• BI Platform Proficiency (Superset, Tableau)
• Stakeholder Management
• Forecasting Techniques
• Statistical Modeling
• Operational Efficiency