Data Scientist - Algorithms, Community Support

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: Airbnb is a mission-driven company 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. As a Data Scientist working on Algorithms in CS, you will have the opportunity to collaborate with a strong team of engineers, product managers, designers and operation agents to enable personalized, fair and exceptional experience for guests & hosts using advanced LLM/ML modeling for Community Support. The Difference You Will Make: We're looking for a talented Data Scientist with LLM/ML expertise to join the Community Support Data Science team. In this role, you'll partner closely with the tech lead to tackle significant components of high-impact projects with a direct opportunity to shape and influence our AI-powered products, differentiated service experiences, and operational optimization strategies. The ideal candidate combines deep technical fluency in LLM/ML with a bias toward action and impact, comfort with ambiguity, and a passion for building scalable, scientific solutions. You’ll work on high-impact projects like: Implement advanced techniques to automate the LLM evaluation process with high efficiency and quality. Scale the high-quality synthetic datasets curation across various CS domains for training and evaluating LLM. Build LLM/ML models to understand customer issues based on diverse datasets and identify failure modes and opportunities for improvement. Build personalization models to offer differentiated experiences and maximize business impact. A Typical Day:  Discover Opportunities: Identify high-impact business opportunities through data exploration and model prototyping, and translate business problems into scientific formulations. Uncover Insights: Analyze structured and unstructured data to uncover meaningful insights and craft actionable proposals that help shape strategy. Build and Ship: Build and deploy production LLM/ML models that directly contribute to the launch of data-driven products, leveraging AI tools to enhance efficiency and impact. Collaborate Cross-Functionally: Build strong relationships with cross-functional partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation. Influence Decisions: Communicate learnings to leaders and stakeholders in a clear, compell