Data Scientist - Inference, Community Support

About Airbnb: 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. Airbnb is a mission-driven marketplace dedicated to creating a world where anyone can belong anywhere. Our Community Support (CS) team is at the heart of that mission—delivering seamless, 10-star customer service experiences complemented by world-class, personalized human support that empowers hosts and guests at every step of their journey.

Position Overview

We are seeking a highly analytical, motivated, and causal inference proficient Data Scientist - Inference, Community Support to join our global Community Support Data Science vertical under a permanent, full-time remote footprint open across the United States. In this high-leverage quantitative seat, you will partner closely beside the area’s tech lead to drive personalized, fair, and exceptional customer experiences using advanced causal inference analysis. Shifting completely away from routine non-regulated data transcription entry logs, basic website modifications, or simple descriptive tracking, you will operate an active high-stakes experiment design, causal machine learning modeling, and multi-objective optimization laboratory. Collaborating across Product, Engineering, Design, and Operations, you will cut through ambiguity to evaluate quality-cost tradeoffs and inform critical platform launch decisions. This position requires a data science authority with 2+ years of industry experience (or a relevant PhD) who structures statistical queries fluidly natively using Data Scientist, Data Analyst, and SQL primitives, commands deep knowledge of experimental design and Bayesian modeling, and translates complex mathematical findings into compelling business narratives independently.

Key Responsibilities

• Causal Inference & Measurement Governance: Design, implement, and scale rigorous causal inference frameworks, statistical models, and quasi-experimental designs to measure the impact of CS product launches natively utilizing Data Scientist best practices.
• Causal ML Modeling Instrumentation: Build, evaluate, and iterate on advanced causal machine learning models to optimize complex budget allocations (such as Make Goods) and uncover heterogeneous treatment effects throughout full model lifecycles.
• Multi-Objective Optimization Triage: Develop analytical frameworks to analyze tradeoffs between competing operational metrics—encompassing accuracy, workflow coverage, support quality, user experience, and financial delivery costs.
• Data Extraction & Processing Operations: Query, manipulate, and structure messy, large-scale transaction databases and user telemetry streams natively leveraging SQL and statistical programming architectures (Python/R).
• Cross-Functional Strategic Synchronization: Build strong collaborative partnerships next to distributed product managers, developers, and operations agents to embed statistical models directly into live production environments.
• Executive Narrative and Decision Influence: Translate highly abstract algorithmic outcomes and statistical limitations into scannable, compelling narratives that empower leadership to make data-driven decisions.
• Domain Capability Evolution: Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision of how science drives platform-wide customer success.

Required Skills & Qualifications

• Possess a formal Master’s degree in a highly quantitative field (such as Statistics, Economics, Computer Science, or a related field) combined with 2+ years of proven industry experience, OR a PhD degree in a matching quantitative discipline.
• Expert Statistical Evaluation Command: Deep, verifiable working literacy in causal inference, experimental design, Bayesian modeling, and statistical inference methodologies.
• Meticulous hands-on experience building, validating, and deploying statistical or machine learning models inside live production environment data pipelines.
• Complete production-grade proficiency writing clean code and manipulating datasets natively utilizing Python or R, along with deep data aggregation skills using SQL.
• Outstanding verbal, written, and textual presentation communication strengths in English, with an established background delivering technical insights simply to non-technical partners.
• Location Context: Position operates under remote guidelines open exclusively to qualified technical inference authorities residing permanently within eligible states inside the United States where Airbnb has a registered corporate entity.

Preferred Strategic Indicators (Nice to Have)

• Prior platform or quantitative analysis background operating directly inside the hospitality tech space, customer care marketplaces, user behavior telemetry, or large-scale two-sided direct commerce networks.
• Prior experience modeling quality-cost optimization variables or managing risk metrics within customer support ecosystems.
• An adaptable, high-agency persona characterized by strong mathematical intuition, a deep bias toward business impact, and an excitement for solving hard, ambiguous human interaction problems.

What We Offer

• Top-Tier US Marketplace Strategic Data Science Remuneration: A highly competitive annual base salary scale of $151,000 — $175,000 USD calibrated precisely to your causal inference pedigree, augmented by high-upside corporate bonuses, equity configurations, and Employee Travel Credits.
• 100% remote workspace infrastructure autonomy open across registered US entities, freeing your timeline from rigid physical office constraints.
• Front-Row Customer Experience Transformation Footprint: Elite professional benchmarks achieved by single-handedly engineering the predictive models and measurement rules that optimize support infrastructure for over 2 billion global guest arrivals.
• Comprehensive health care protection choices, coupled with modern wellness frameworks and fully disability-inclusive environment paths.
• Access to a legendary company culture built for international collaboration, clear async communication, shared ownership, and a low-bureaucracy engineering ecosystem that respects data-driven innovation and values continuous personal growth.