Senior Data Scientist, People Analytics & Research
Airbnb Remote - USAEst. Est. USD 140,000–190,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Sql
- Llm
- Data Science
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
The Community You Will Join:
People Analytics & Research is a strong team of Data Scientists, Data Engineers, and Analysts. Our work is highly sought-after, and impacts stakeholders in our People function, and across the business. In this role, you'll take on some of the hardest questions about Airbnb's workforce - how we recruit, pay, develop, and retain our people - partnering with leaders across Recruiting, Compensation, Talent, and the wider business to turn rigorous analysis into decisions they act on.
The Difference You Will Make:
The People Analytics & Research team is looking for an experienced Data Scientist to lead and/or contribute to our most important research - applying causal inference and quasi-experimental methods to high-stakes people questions: how we recruit, hire, promote, and retain a best-in-class workforce; how we keep key company processes fair; and how work itself is changing. Employee listening and survey analysis are part of the mix, but the heart of the role is rigorous inferential research on observational people data. The role is highly cross-functional, and you will partner with Recruiting, Talent Leaders, Compensation, Legal, and Diversity & Belonging. We need a Data Scientist with a proven track record of translating data into insight and action.
If you have a proven background in this field and are excited to help build Airbnb’s community, we want to hear from you.
A Typical Day:
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
Your Expertise:
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
Your Location:
This position is US - Remote Eligible. The role may include occasional work at an Airbn
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