Data Scientist, Inference (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, and Engineering to provide actionable recommendations and tools based on effective, timely, and granular measurements.

The difference you will make

We are seeking an experienced Data Scientist with deep expertise in causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.

Key expectations:

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

A typical day / Responsibilities

• Apply and develop causal inference methods to estimate the effectiveness of Airbnb’s marketing initiatives (experimental and observational approaches).
• 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) to provide insights that optimize marketing strategies.
• Lead the creation of internal white papers and contribute to Airbnb tech blog posts.

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).
• 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; interest in staying informed about the latest academic research.
• Familiarity with Bayesian modeling and its applications in marketing.
• Experience with causal ML modeling.
• Experience developing end-to-end models for data-driven decision-making.

Location & working arrangement

• 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.
• You must live in a state where Airbnb, Inc. has a registered entity (the posting links to Airbnb careers for the up-to-date list of excluded states).
• If employed by another Airbnb entity, your recruiter will inform you of eligible states.

Compensation & benefits

• Base pay range: $148,000—$174,000 USD (the actual base pay depends on factors such as training, transferable skills, work experience, business needs and market demands).
• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Inclusion & accommodations

• Airbnb is committed to diversity and inclusion and encourages all qualified individuals to apply.
• Reasonable accommodations for candidates with disabilities are available by contacting [email protected] with role details and accommodation needs.