About the job
Founded in 2007, Airbnb began its journey when two hosts welcomed three guests into their San Francisco home. Today, Airbnb has grown into a global platform with over 5 million hosts who have welcomed more than 2 billion guests in nearly every country around the world. Each day, hosts offer unique stays and experiences that allow guests to connect with communities in a more authentic and meaningful way.
Join Our Community:
The MarTech Data Science Measurement team plays a pivotal role in enabling Airbnb to maximize marketing return on investment (ROI) through data-driven insights. We lead efforts in defining and evolving best practices for assessing and enhancing marketing impact. Collaborating closely with Marketing, Finance, and Engineering, we provide actionable recommendations and tools based on precise, timely, and granular measurements. Our team's core principles include:
- Actionable: Deliver insights that inspire confident business decisions.
- Impactful: Focus on projects that hold significant value for Airbnb.
- Balanced: Tailor methodologies to address business questions and data realities, recognizing inherent limitations.
- Rigorous: Uphold methodological integrity and quantify the sensitivity of our findings.
- Innovative: Commit to advancing measurement science and developing new methodologies.
- Influential: Share knowledge across Airbnb and the broader data science community.
Your Impact:
We are looking for a seasoned (Contract) Senior Data Scientist to join us for a 24-month contract. The ideal candidate will have extensive expertise in marketing measurement, particularly in Marketing Mix Modeling (MMM) and geo-based causal inference. You should possess a robust statistical intuition and hands-on modeling experience to quantify the incremental impact of Airbnb's marketing investments across various channels and regions. Proficiency in Python and familiarity with Bayesian frameworks are essential, along with the ability to distill complex measurement findings into clear, actionable recommendations for senior stakeholders.
A Day in the Life:
- Marketing Mix Modeling: Design, build, and maintain MMM models to estimate incremental contributions from various channels, including prior elicitation, adstock/saturation modeling, validation, and sensitivity analysis.
- Geo-Based Measurement: Develop and analyze geo-experiments (such as synthetic control and difference-in-differences) to assess marketing incrementality and validate MMM outputs.
- Measurement Infrastructure: Construct and uphold data pipelines that support robust marketing measurement initiatives.

