This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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.
Job Responsibility:
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
Nice to have:
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