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 MarTech Data Science Measurement team empowers Airbnb to optimize marketing ROI by generating data-driven recommendations. We define and advance best practices for measuring and optimizing marketing impact, collaborating with Marketing, Finance, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements. Our team's tenets include delivering Actionable insights, prioritizing Impactful projects, maintaining Balanced methods, ensuring Rigorous integrity, fostering Innovative advancements, and sharing Influential learnings.
About the Role
We are seeking an experienced (Contract) Sr. Data Scientist for a 24-month contract with deep expertise in marketing measurement, particularly in Marketing Mix Modeling (MMM) and geo-based causal inference. The ideal candidate will bring strong statistical intuition and hands-on modeling experience to quantify the incremental impact of Airbnb's marketing investments across channels and geographies. You should be fluent in Python, comfortable working with Bayesian frameworks, and capable of translating complex measurement findings into clear, actionable recommendations for senior stakeholders.
Responsibilities
- 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.
Requirements
- 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.