Role overview
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 Community You Will Join:
MarTech Data Science Measurement empowers Airbnb to optimize marketing ROI by generating data-driven recommendations. We lead the way in defining and advancing best practices for measuring and optimizing marketing impact. We collaborate with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements.
Our team’s tenets are:
- Actionable: Deliver insights that drive confident business decisions.
- Impactful: Prioritize projects based on their expected value to Airbnb.
- Balanced: Adapt methods to business questions and data realities, acknowledging limitations.
- Rigorous: Maintain methodological integrity and quantify the sensitivity of findings.
- Innovative: Invest in advancing measurement science and developing new methods.
- Influential: Share learnings across Airbnb and the broader data science community.
The Difference You Will Make:
We are seeking an experienced (Contract) Sr. Data Scientist for a 24 month contract with deep expertise in marketing measurement, with a particular focus on Marketing Mix Modeling (MMM) and geo-based causal inference. The ideal candidate brings strong statistical intuition and hands-on modeling experience to quantify the incremental impact of Airbnb's marketing investments across channels and geographies. They are fluent in Python, comfortable working with Bayesian frameworks, and can translate complex measurement findings into clear, actionable recommendations for senior stakeholders.
A Typical Day:
- Marketing Mix Modeling: Design, build, and maintain MMM models that estimate incremental channel contributions, including prior elicitation, adstock/saturation modeling, validation, and sensitivity analysis.
- Geo-Based Measurement: Develop and analyze geo-experiments (synthetic control, difference-in-differences) to measure marketing incrementality and validate MMM outputs.
- Measurement Infrastructure: Build and maintain data pipelines and automated measurement systems ensuring reproducibility and scale.
- AI-Accelerated Prototyping: Use AI agent workflows to rapidly develop v0 prototypes and spec-driven model implementations — compressing weeks of iteration into days.
- Productionalization: Refine research prototypes into production-grade systems with proper unit testing, data validation, and code review standards.
- Insight Communication: Translate complex measurement findings into clear narratives and confident budget recommendations for Marketing and Finance stakeholders.
Your Expertise:
- 5+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (computer science, statistics etc.), or 2+ years of experience with a Ph.D.
- Deep, hands-on experience building and validating Marketing Mix Models in a production setting.
- Strong working knowledge of causal inference methods, including geo-experimentation and observational approaches.
- Proficiency in Python and R for statistical modeling, and SQL for data manipulation.
- Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
- Proven track record of solving business problems through data science methods.
Preferred Expertise:
- Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field.
- Familiarity with Bayesian modeling and its applications in marketing.
- Working knowledge of AI coding agents for accelerating prototyping, spec-driven development, and multi-agent workflows.
- Experience in developing end-to-end models for data-driven decision-making.