Lead Advanced Analyst, Integrated Marketing

Airbnb

12d•$164,000 - $191,000•Remote

About The Position

The Integrated Marketing Analyst sits within Marketing Analytics and serves as the measurement engine for Airbnb's cross-channel growth initiatives, spanning Search, Growth Media, Affiliates, and Guest Engagement across Homes, Experiences, Services, and Hotels, as well as emerging pilots. You'll partner closely with Marketing, Creative, Data Science, and Finance to prove incrementality and optimize investment across a fast-moving, test-and-learn portfolio.

Requirements

Experience: 6+ years in analytics or data science, with depth in marketing, growth, or lifecycle/loyalty analytics.
Experimentation expertise: Strong background in causal inference and designing experiments and holdouts for multi-touchpoint marketing programs.
Insights & Influence: A track record of insights that directly shape strategy, roadmaps, and budget decisions at a senior level.
Communication: Excellent ability to translate complex analytical trade-offs into clear, confident recommendations for senior, cross-functional stakeholders.
Technical skills: Advanced proficiency in SQL and Python or R, with experience working in large-scale data environments and building scalable reporting tools.
Modern toolkit: Experience using AI tools to accelerate analysis and build scalable solutions.
Adaptability: Comfort operating with ambiguity across a fast-paced, evolving portfolio of initiatives spanning multiple business lines.
Education: Quantitative degree required.

Responsibilities

Own measurement strategy: Design and lead the end-to-end measurement plan for a major loyalty/community pilot, including multi-arm testing across benefits, credits, and offers.
Design and analyze experiments: Owning experimentation end to end, write experiment plans and analyze the results.
Conducting analysis to deliver actionable insights: Surface findings on customer segments, timing, and creative performance that inform decisions on scaling the program and where to prioritize.
Collaborate with cross-functional partners: Partner with marketing, operations, finance, data science, and product to support a data-driven strategy for marketing, share results, and influence decisions through data.
Present to leadership: Deliver clear, decision-ready readouts to senior marketing and cross-functional leadership on program and campaign effectiveness.
Expand scope over time: As testing needs ease, apply the same experimentation approach to support other growth marketing priorities across additional lines of business.