Data Scientist – Causal Inference & Community Support

Data Scientist – Causal Inference & Community Support (Remote US)

Airbnb is hiring a Data Scientist with strong causal-inference expertise to join its Community Support Data Science team. This U.S. Remote Eligible role focuses on rigorous experimentation, causal machine learning, statistical inference, and optimization to improve support experiences for Airbnb hosts and guests.

You will collaborate with engineers, product managers, designers, operations teams, analytics partners, and technical leadership on projects involving AI-powered products, differentiated customer service, operational optimization, and high-stakes product decisions.

Job Overview

Company: Airbnb

Team: Community Support Data Science

Work Arrangement: US – Remote Eligible

Location: United States

Experience: 2+ years with a relevant Master’s degree, or relevant PhD

Base Salary: $151,000–$175,000 USD per year

Additional Compensation: Role may also be eligible for bonus and equity

The Data Scientist will design experiments and quasi-experiments, build causal machine-learning models, quantify the long-term effects of product changes, investigate heterogeneous treatment effects, and provide strategic analysis that helps Airbnb improve Community Support quality, personalization, efficiency, and cost effectiveness.

Key Responsibilities

Causal Inference & Measurement

• Design rigorous experiments to measure the causal impact of Community Support product launches.
• Develop quasi-experimental approaches when conventional randomized experiments are not appropriate.
• Build causal-inference frameworks and statistical models for measuring interventions.
• Evaluate system and product performance using statistically rigorous methods.
• Use causal analysis to support data-informed product-launch decisions.
• Quantify the long-term effects of product and operational changes.
• Identify and analyze heterogeneous treatment effects.
• Surface opportunities for improving Community Support outcomes.

Machine Learning & Modeling

• Build causal machine-learning models for high-impact business decisions.
• Develop models that help optimize Make Goods budget allocation.
• Evaluate and iterate on statistical and machine-learning models.
• Apply strong modeling practices across the complete model lifecycle.
• Perform feature engineering.
• Support production deployment of statistical and ML models.

Optimization & Decision Science

• Develop frameworks for evaluating tradeoffs between competing objectives.
• Analyze accuracy, coverage, user experience, and operational cost.
• Identify strategies that improve overall Community Support effectiveness.
• Deliver strategic analysis of quality-versus-cost tradeoffs.
• Help leadership make evidence-based decisions about support products and operations.

Cross-Functional Collaboration

• Partner with Product teams on high-impact decisions.
• Collaborate with Design and Engineering.
• Work closely with Community Support Operations and Analytics.
• Build strong relationships across technical and operational teams.
• Communicate analytical findings to leaders and stakeholders.
• Translate complex statistical findings into clear, decision-oriented narratives.
• Help evolve and scale data-science capabilities across the Community Support domain.

Required Qualifications

• 2+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative discipline, or a PhD in a relevant field.
• Relevant quantitative fields may include statistics, economics, computer science, or related disciplines.
• Strong knowledge of causal inference.
• Strong experimental-design expertise.
• Strong understanding of Bayesian modeling.
• Strong statistical-inference knowledge.
• Hands-on experience building statistical or machine-learning models.
• Experience deploying statistical or ML models in production environments.
• Statistical programming skills using Python or R.
• Strong SQL and database skills.
• Ability to communicate effectively with audiences at different technical levels.
• Ability to turn complex analytical findings into compelling narratives and recommendations.
• Strong project-management skills.
• Strong collaboration and communication skills.

Technical & Analytical Focus

• Causal inference
• Experimental design
• Quasi-experiments
• Causal machine learning
• Bayesian modeling
• Statistical inference
• Heterogeneous treatment effects
• Predictive and statistical modeling
• Feature engineering
• Production ML
• Optimization
• Python
• R
• SQL

Community Support & AI

This position applies data science to Airbnb’s Community Support organization, which provides support experiences for hosts and guests.

The Data Scientist will contribute to projects spanning AI-powered products, differentiated service, and operations optimization. The role uses causal inference and statistical modeling to determine whether interventions genuinely improve customer and business outcomes rather than relying only on correlation.

Experimentation & Product Decisions

A central responsibility is designing experiments and quasi-experiments that measure the causal impact of product launches and operational changes.

The resulting evidence will help Product, Engineering, Operations, and leadership determine whether initiatives should launch, how they should evolve, and which customer populations benefit most from particular interventions.

Causal Machine Learning

The role includes building causal ML models that influence high-stakes decisions, including how resources such as Make Goods budgets are allocated.

Candidates should be comfortable working across the model lifecycle, including feature engineering, model development, evaluation, iteration, and production deployment.

Remote Work & Location Eligibility

This position is explicitly designated as U.S. Remote Eligible.

Remote eligibility is not unrestricted across every U.S. location. Candidates must live in a state where Airbnb, Inc. has a registered entity. If employment is through another Airbnb entity, the recruiter will confirm the applicable state eligibility requirements.

Airbnb maintains an evolving list of excluded states on its careers site, so candidates should confirm their current location eligibility when applying.

The position may also involve occasional work from an Airbnb office or attendance at company or team offsites as agreed with the manager.

Compensation

The stated base-pay range for this position is $151,000–$175,000 USD per year.

Actual base compensation depends on factors including training, transferable skills, professional experience, business needs, and market conditions.

The role may also be eligible for bonus compensation, equity, employee benefits, and Airbnb Employee Travel Credits.

Inclusive Hiring & Accommodations

Airbnb states that it is committed to an inclusive application and interview process and provides reasonable accommodations for candidates with disabilities who require assistance completing the application process.

Apply for the Data Scientist – Causal Inference Role

U.S.-based data scientists with strong causal-inference, experimentation, Bayesian modeling, Python or R, SQL, and production modeling experience can review the complete opportunity and apply through Airbnb’s provided careers page.

Worker Relationship: Employee

Work Arrangement: U.S. Remote Eligible

Location: United States – eligible Airbnb employment states only

Team: Community Support Data Science

Industry: Technology / Marketplace / Travel

Education: Master’s degree in a quantitative field plus 2+ years of relevant industry experience, or relevant PhD

Experience: 2+ years where Master’s pathway applies

Compensation: $151,000–$175,000 USD base salary; potential bonus, equity, benefits, and Employee Travel Credits

Job Apply Link:
https://careers.airbnb.com/positions/8031907/