Description
We are seeking a motivated and talented Data Scientist with strong causal inference expertise to join the Community Support Data Science team at Airbnb. As a Data Scientist working on Causal Inference in Community Support, you will collaborate with a strong team of engineers, product managers, designers, and operation agents to enable personalized, fair, and exceptional experiences for guests and hosts using advanced causal inference analysis.
The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity to drive clarity in complex problem spaces. You’ll work on high-impact projects like designing rigorous experiments and quasi-experiments to measure the causal impact of Community Support product launches, building causal ML models to optimize budget allocation, conducting causal inference analyses to quantify the long-term effects of product changes, and delivering strategic insights on quality-cost tradeoffs.
Responsibilities:
- Design and implement causal inference frameworks and statistical models to measure the impact of interventions, evaluate system performance, and uncover opportunities for improvement.
- Build, evaluate, and iterate on causal ML models that power high-stakes decisions, applying best practices across the full model lifecycle.
- Develop frameworks to analyze tradeoffs between competing objectives and propose strategies to improve overall effectiveness.
- Collaborate cross-functionally with Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation.
- Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed, data-driven decision-making.
- Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes.
Requirements:
- 2+ years of industry experience in a quantitative analysis role with a Master's degree in a quantitative field, or PhD in relevant fields.
- Strong knowledge of causal inference and experimental design.
- Strong knowledge of Bayesian modeling and statistical inference.
- Hands-on experience building and deploying statistical or ML models in production environments.
- Skilled in statistical programming (Python/R) and database usage (SQL).
- Proven ability to communicate clearly and effectively to audiences of varying technical levels.
- Ability to translate complex findings into compelling narratives that drive impact.
- Excellent project management, communication, and collaboration skills.
Benefits:
- The base pay range is $151,000-$175,000 USD.
- This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.