Staff Advanced Analyst, Guest Engagement

Airbnb

1d•$180,000 - $221,000•Remote

About The Position

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. The Guest Engagement AA sits within Marketing Analytics and serves as the analytical backbone for Airbnb's lifecycle marketing programs — the email, push, and in-app communications that reach hundreds of millions of guests across their entire journey. You'll partner closely with Guest Engagement Marketing, MarTech Data Science, and Strategic Finance to drive measurable booking impact through experimentation and insights. You will be the clear analytics owner of Airbnb's guest lifecycle marketing domain — covering abandon journeys, demand generation, onboarding, upsell, and more. This role is expected to drive significant incremental bookings in 2026 by setting the analytics strategy, designing rigorous experiments, and surfacing proactive insights across 30+ active programs.

Requirements

9+ years in analytics or data science, with depth in marketing and/or growth analytics.
Analysis that drives action: Your insights directly shape what teams build, test, and invest in — you influence roadmaps and prioritization at the Director level.
Strong experimentation skills: Experience designing and interpreting A/B tests and measurement frameworks for multi-channel marketing programs.
Excellent communicator: Able to distill complex findings into clear, compelling recommendations for senior stakeholders. Comfortable pushing back when the data

Responsibilities

Own the analytics roadmap for Guest Engagement — define what to measure, what to test, and where the biggest opportunities lie across the full guest lifecycle. Specific projects and prioritization decisions should exist because of your recommendations.
Design and analyze experiments at scale across abandon journeys, demand gen ML model rollouts, and placement-level A/B tests. Develop measurement frameworks (holdouts, proxy metrics, annualized impact models) to accurately attribute cumulative program impact.
Surface proactive insights that go beyond reporting — user segmentation, funnel analysis, fatigue signals, channel optimization — and translate them into strategic recommendations for Director-level marketing leaders.
Build scalable, self-serve reporting (dashboards, OKR tracking, experiment trackers) that empowers partners and frees AA capacity for higher-leverage work.
Collaborate cross-functionally with MarTech DS on ML model feedback loops and attribution, with SF&A on goal methodology, and with India-based analytics resources on operational reporting.