Remote opportunity at
AirbnbSenior Data Scientist, People Analytics & Research
Airbnb operates a global platform connecting travelers with hosts who offer unique accommodations and experiences. The organization is currently seeking a Senior Data Scientist to join…
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About This Role
Airbnb operates a global platform connecting travelers with hosts who offer unique accommodations and experiences. The organization is currently seeking a Senior Data Scientist to join the People Analytics & Research team. In this capacity, the professional will tackle complex workforce questions by analyzing observational data and applying causal inference methods to topics such as recruitment, talent retention, promotions, and compensation structures. This position collaborates extensively with various departments, including…
Job Description
Airbnb operates a global platform connecting travelers with hosts who offer unique accommodations and experiences. The organization is currently seeking a Senior Data Scientist to join the People Analytics & Research team. In this capacity, the professional will tackle complex workforce questions by analyzing observational data and applying causal inference methods to topics such as recruitment, talent retention, promotions, and compensation structures.
This position collaborates extensively with various departments, including Legal, Recruiting, Compensation, and Diversity & Belonging. Daily duties involve gathering workforce data, executing statistical models, designing metrics such as quality-of-hire, managing compensation analytics, and leveraging artificial intelligence tools like LLM-based agents to accelerate analytical research. The role suits quantitative professionals experienced in translating workforce data into strategic action.
Responsibilities
- Collaborate with internal partners to understand workforce challenges and gather relevant employee data
- Apply statistical models and data science methodologies to analyze hiring, retention, promotions, compensation, and productivity
- Create visual reports and data narratives to guide decision-making for business leaders
- Manage recurring compensation analytics and legally sensitive analyses in coordination with Employment Legal and Total Rewards
- Design and measure the quality-of-hire metric alongside the Recruiting team while handling statutory and governance reporting
- Utilize artificial intelligence platforms and language models to speed up prototyping and data synthesis
Requirements
- Minimum of five years of industry experience
- Master's degree or PhD in a quantitative discipline
- Hands-on expertise with causal inference on observational data and quasi-experimental research designs
- Strong proficiency in SQL for data access, along with R or Python for statistical analysis
- Demonstrated background in applying data science to workforce, recruiting, or compensation questions involving sensitive data
- Reside in a U.S. state where Airbnb, Inc. maintains a registered entity and permits remote work
- Capability to communicate technical insights clearly to cross-functional stakeholders
Qualifications
- Familiarity with survey design and analysis as part of a broader research toolkit
Core Skills
Benefits
- Base salary between USD 180,000 and 210,000 per year
- Eligibility for bonuses, equity, benefits, and Employee Travel Credits
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, this role is remote-eligible within the United States, provided the candidate resides in a state where Airbnb has a registered entity and allows employment. Occasional travel to an Airbnb office or offsite may be required.
What is the salary range for this role?
The annual base pay ranges from USD 180,000 to 210,000. Actual compensation depends on transferable skills, experience, training, business needs, and market demands.
What qualifications are needed to apply?
Applicants must have a Master's degree or PhD in a quantitative field, at least five years of industry experience, deep expertise in causal inference on observational data, and proficiency in SQL and either R or Python.
Sample Interview Questions
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