Senior Data Scientist, People Analytics & Research

Airbnb is hiring a Senior Data Scientist for its People Analytics & Research team. The role applies causal inference and other rigorous research methods to workforce questions, leading compensation analytics and quality-of-hire measurement while turning findings into decisions with cross-functional partners.

Responsibilities:

• Collaborate with partners and stakeholders to understand people-related business problems, and gather relevant people data to analyze
• Utilize appropriate statistical models and data science methodologies to gain insights, explain, or predict a wide variety of people-related processes, such as recruiting and hiring, promotion, retention, pay equity, productivity, and organizational effectiveness, among others
• Translate data and insights into meaningful visualizations and stories to drive strategy, action, and decision-making with leaders across the business
• Align research priorities with business priorities and take a customer-focused mindset in working with stakeholders
• Lead the team's compensation analytics - the recurring, legally sensitive analyses that inform Total Rewards decisions on pay, compensation structure, and talent awards - in close partnership with Employment Legal and Total Rewards
• Lead design and measurement of Airbnb's quality-of-hire metric with Recruiting, and own sensitive statutory and governance reporting
• Be a constant learner, active listener, and teacher to advance data science, people analytics, and Airbnb
• Use AI fluently - including the team's AirPanda platform and LLM-based agents - to accelerate analysis, prototyping, and synthesis, and to extend what a single researcher can deliver

Requirements:

• 5+ years in industry experience and a Master's degree/PhD in a quantitative field
• Deep experience with causal inference on observational data and quasi-experimental research design and analysis
• Proficiency in R or Python for statistical analysis, and SQL for data access
• Familiarity with survey design and analysis, as one of several methods in the toolkit
• Experience applying data science to compensation, recruiting, or broader workforce and organizational questions, including work with legally sensitive data
• Ability to communicate clearly and effectively to cross functional partners of varying technical levels and drive impact
• Experience working with large practical datasets