(contract) Senior Data Scientist, Platform Inference - Martech Ds Measurement

Airbnb Airbnb · Consumer · United States · Data Science

This role focuses on building and maintaining marketing measurement systems, including Marketing Mix Models and geo-based causal inference. It also involves using AI agent workflows for rapid prototyping and productionalizing research prototypes into scalable systems.

What you'd actually do

  1. Marketing Mix Modeling: Design, build, and maintain MMM models that estimate incremental channel contributions, including prior elicitation, adstock/saturation modeling, validation, and sensitivity analysis.
  2. Geo-Based Measurement: Develop and analyze geo-experiments (synthetic control, difference-in-differences) to measure marketing incrementality and validate MMM outputs.
  3. Measurement Infrastructure: Build and maintain data pipelines and automated measurement systems ensuring reproducibility and scale.
  4. AI-Accelerated Prototyping: Use AI agent workflows to rapidly develop v0 prototypes and spec-driven model implementations — compressing weeks of iteration into days.
  5. Productionalization: Refine research prototypes into production-grade systems with proper unit testing, data validation, and code review standards.

Skills

Required

  • 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.

What the JD emphasized

  • 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.
  • Working knowledge of AI coding agents for accelerating prototyping, spec-driven development, and multi-agent workflows.

Other signals

  • AI agent workflows for prototyping
  • Marketing Mix Modeling
  • Geo-based causal inference
  • Productionalization of research prototypes