Causal Data Scientist, Platform — Remote

Airbnb; United States; Remote; USD 151,000 - 175,000; Full time

Benefits offered by this job

Bonus eligibility

Equity

Employee Travel Credits

Remote-friendly

Job summary

Airbnb is seeking a Data Scientist to advance causal inference in Community Support, enabling personalized and fair experiences for hosts and guests. You will design experiments, build causal ML models, and collaborate with product, design, engineering, and analytics to inform decision-making.

The role is US-based with remote eligibility. Candidates should have a strong background in causal inference, Bayesian methods, and production ML deployment, with excellent communication and

Qualifications

• 2+ years of industry experience in quantitative analysis.
• 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 Python and/or R and SQL.
• Able to communicate complex findings clearly to diverse audiences.
• Excellent project management and collaboration skills.

Responsibilities

• Design rigorous experiments and quasi-experiments to measure causal impact of CS launches.
• Build causal ML models to optimize budget allocation and drive impact.
• Conduct causal analyses to quantify long-term effects of product changes.
• Deliver strategic insights to leadership for data-driven decisions.
• Collaborate with cross-functional partners to drive experimentation and measurement.

Skills

Causal inference

Bayesian modeling

Statistical inference

Python/R

SQL

Communication

Project management

Collaboration

Education

Master's in quantitative field

PhD in relevant fields

Tools

SQL

Job description

Airbnb is seeking a Data Scientist to advance causal inference in Community Support, enabling personalized and fair experiences for hosts and guests. You will design experiments, build causal ML models, and collaborate with product, design, engineering, and analytics to inform decision-making.

The role is US-based with remote eligibility. Candidates should have a strong background in causal inference, Bayesian methods, and production ML deployment, with excellent communication and