Data Scientist, Platform - Martech

Details

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

MarTech Data Science Measurement empowers Airbnb to optimize marketing ROI through data-informed decision-making. The team defines and advances best practices for measuring and optimizing marketing impact and collaborates with Marketing, Finance, Engineering, and Product to provide actionable recommendations and tools based on effective, timely, and granular measurements.

The Difference You Will Make

We are seeking experienced Data Scientists to serve as technical anchors across the team’s two pillars. The ideal candidate combines depth in causal inference, experimentation, and customer relationship modeling with the ability to drive rigor in solutions and data-informed decision making across the team and cross-functional partners.

Key attributes:

• Actionable: Deliver insights that drive confident business decisions.
• Impactful: Prioritize projects based on their expected value to Airbnb.
• Balanced: Adapt methods to business questions and data realities, acknowledging limitations.
• Rigorous: Maintain methodological integrity and quantify the sensitivity of findings.
• Innovative: Invest in advancing measurement science and developing new methods.
• Influential: Share learnings across Airbnb and the broader data science community.

Responsibilities

• Apply and develop causal inference methods to estimate the effectiveness of Airbnb’s marketing initiatives.
• Conduct data pulls, analyze trends, and create new features to support measurement efforts.
• Design and analyze experiments to evaluate the impact of marketing campaigns.
• Work effectively with cross-functional teams (Marketing, Finance, Engineering, Product) to provide insights that optimize marketing strategies.
• Lead creation of internal white papers and contribute to Airbnb tech blog posts; provide thought leadership in measurement science.

Requirements

• PhD in Economics, Statistics, Marketing, or a related field OR a Master’s degree in a similar field with 2+ years of experience.
• Deep knowledge of causal inference methodologies and experimentation techniques.
• Proficiency in statistical programming (Python or R) and database usage (SQL); experience with agentic coding.
• Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
• Proven track record of solving business problems through data science methods.

Preferred Expertise

• PhD in Economics, Statistics, Marketing, or a related field (preferred).
• Passion for marketing and consumer science, with a desire to stay informed about the latest academic research.
• Familiarity with Bayesian modeling and its applications in marketing.
• Experience with causal ML modeling.
• Experience in developing end-to-end models for data-driven decision-making.

Location

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. While Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity (see Airbnb careers site for excluded states). If employed by another Airbnb entity, your recruiter will inform you of eligible states.

Inclusion & Accessibility

Airbnb is committed to working with the broadest talent pool possible and provides a disability inclusive application and interview process. Candidates who require reasonable accommodation can contact [email protected] with their full name, the role, and the accommodation needed.

Compensation & Benefits

The actual base pay depends on factors such as training, transferable skills, work experience, business needs and market demands. This role may be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range

$151,000—$175,000 USD

Offices: United States