Staff Data Scientist, Guest & Host

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:

You will join the Guest and Host Data Science organization, which powers products and data-driven decisions over Airbnb’s marketplace of Guest and Hosts. You will join a collaborative team of data scientists, analysts, engineers, product managers and designers who build, launch and iterate on our product roadmap to drive growth and deeper sophistication through experimentation, modeling, foundational tools and insights. Our work is core to ensuring that Airbnb’s strategy roadmap stays highly relevant for our users while supporting the long-term health of our marketplace. We work directly with decision makers in engineering and product to develop data-driven frameworks, technical solutions, evaluate product changes and guide the company through rigorous measurement and modeling.

The Difference You Will Make:

Under this general application, you will be considered for applications over several tracks.

Growth Product Data Science

• Partner directly on growth initiatives to build, ship, measure incrementality of bookings/attach rate/revenue, and optimize 0-to-1 customer-facing features
• Thought partnership with Product to define strategy, sequence iteration, scale impact via science frameworks and as the go-to tech lead around data, experimentation, and domain understanding
• Build observational causal inference models to deeply understand guest intent, identify underlying mechanisms, and build data products to measure impact, and inform feature objectives and tradeoffs 
• Champion AI-enabled Product Understanding, to scale data-driven frameworks, robust measurement, and compelling storytelling of data learnings to guide recommendations and roadmaps with senior leaders

Pricing Data Science

• Develop a pricing guidance system for hosts as well as experimental and observational methods to measure the impact of pricing feature launches.
• Collaborate with product and cross-functional teams to pioneer pricing strategies and translate advanced modeling into actionable recommendations
• Develop foundational models and experimental approaches that balance supply and demand in the marketplace, leveraging empirical methods to assess and iterate on pricing feature impact
• Craft compelling data narratives to surface actionable insights, empower data-driven decision making and influence the future direction of Airbnb’s pricing ecosystem

Marketplace Optimization and Ranking

• Develop models and analytic frameworks that improve listing ranking and recommendation. This includes incorporating marketplace dynamics such as listing availability, supply quality, and long-term ecosystem health into ranking decisions.
• Partner closely with Machine Learning Engineers and Product to launch high-impact search improvements. Design experiments and evaluation frameworks to understand the impact of search and AI-driven product improvements.
• Build scalable data products and modeling pipelines that power ranking features, query understanding, and personalization. Your work will help enable the next generation of AI-powered search experiences at Airbnb
• Connect marketplace thinking, modeling, and experimentation across teams and set the technical direction for modeling and experimentation in search, ranking and personalization.

The ideal candidate will be curious, optimistic, and relentless at leading innovation in using AI tools to scale experimentation and data-driven decisions, development of domain-relevant input metrics, and continuous understanding of tradeoffs and end-to-end guest product journeys. You will hold a high bar for customer experience and a strong desire to accurately understand user behavior and drive business growth over both Homes and non-Homes verticals. 

Your expertise:

• Causal inference expertise. Experience with machine learning techniques in a marketplace product setting
• 9+ years of relevant industry experience and a Master’s degree or PhD in a quantitative field
• Strong coding skills in SQL and either Python or R.
• Comfort with building proof-of-concept prototypes. Passionate about AI and possessing a learner’s attitude.
• Proven ability to be driven and succeed in collaborative environments with cross-functional stakeholders and also in independent work settings. Ability to autonomously set a roadmap for business impact.
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity.Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. 

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

Equal Employment Opportunity:

Airbnb values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Airbnb are considered without regard to race, color, religion, national origin, age, gender, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, gender expression, sexual orientation, or any other legally protected characteristic.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.  

Pay Range

$200,000—$242,000 USD

Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @airbnb.com or @ ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing.  We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.