# Lead, Advanced Analytics, Fraud and Safety Operations

**Company:** [Airbnb](https://hotfix.jobs/companies/airbnb)
**Location:** Remote
**Role:** Data Analytics
**Salary:** $164k – $191k/yr
**Experience:** 5+ years
**Skills:** SQL, Python, R, Machine Learning, Causal Inference, Experiment Design, Data Modeling, Statistical Analysis, Anomaly Detection, Graph Analytics
**Posted:** 2026-06-19

> Lead advanced analytics for fraud and safety at Airbnb. Build self-service data tools, design experiments, and create dashboards to help cross-functional teams make data-driven decisions on risk and policy.

## Job Description

## Responsibilities
- 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
- 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

## Requirements
- 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

## 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
- Exposure to adjacent trust / risk domains, such as identity verification, fraud, chargebacks, or financial risk management
- Graduate degree (MS/PhD) in statistics, economics, computer science, data science, operations research or another quantitative field

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