Staff Data Scientist - Long Term Impact

Airbnb Airbnb · Consumer · United States · Data Science

This role focuses on developing and improving frameworks for estimating the long-term causal impact of product changes at Airbnb. It involves applying advanced causal inference methods, including experimental, econometric regression, and quasi-experimental techniques, to measure platform/product impacts and optimize for long-term business outcomes. The role requires strong programming skills and experience in quantitative fields.

What you'd actually do

  1. Develop causal estimates for long-term impact of short-term metric movements.
  2. Build frameworks for estimating how the impact of product changes evolves over time.
  3. Create frameworks and tooling to evaluate the heterogeneous impact of product changes
  4. Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts.

Skills

Required

  • Advanced degree in a quantitative field (Operations Research, Economics, Mathematics, Physics)
  • Proven ability to design analytical solutions to complex problems with real world applications
  • Familiarity with recent developments in causal inference
  • 6+ years (with Ph.D) or 8+ yrs (with Masters) of experience of working or doing research in one or more experimentation / causal inference domains
  • Strong programming (R, Python / Scala / Java / C++ or equivalent) skills
  • Versatility to communicate clearly with both technical and non-technical audiences

Nice to have

  • Publications or presentations in recognized Data Science journals/conferences

What the JD emphasized

  • long-term impact estimation
  • frameworks for estimating how the impact of product changes evolves over time
  • evaluate the heterogeneous impact of product changes
  • Develop and apply causal inference methods