Senior Data Scientist, People Analytics & Research

Airbnb · Remote (Remote US)

Equity This posting mentions equity, such as stock options or RSUs. The terms are on the company’s site.

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About the role

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

Continued in Airbnb’s original posting ↗.

Before you apply. Check the location rules in the full posting: many remote roles are open only to people in certain countries or US states, and some need occasional travel. Listings are sourced from each company’s own careers site and updated daily. Apply on the company site. How to spot a fake job · Report this listing

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