Data Scientist - Inference, Community Support

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">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.</span></p></div><p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>The Community You Will Join: </strong></span></p> <p>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.</p> <p>As a Data Scientist working on Causal Inference 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 &amp; hosts using advanced causal inference analysis for Community Support.</p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>The Difference You Will Make:</strong></span></p> <p>We're looking for a motivated and talented Data Scientist with strong causal inference expertise to join the Community Support Data Science team. You'll partner closely with the area's tech lead on high-impact projects spanning AI-powered products, differentiated service, and operations optimization.</p> <p>The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity to drive clarity in complex problem spaces. You’ll work on high-impact projects like:</p> <ul> <li>Design rigorous experiments &amp; quasi-experiments to measure the causal impact of CS product launches and drive data-informed launch decisions.</li> <li>Build causal ML models to optimize Make Goods budget allocation and maximize business impact.</li> <li>Conduct causal inference analyses to quantify the long-term effects of product changes and uncover heterogeneous treatment effects.</li> <li>Deliver strategic insights on quality-cost tradeoffs, empowering leadership to deliver the best possible support experience to our community.</li> </ul> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>A Typical Day:&nbsp;</strong></span></p> <ul> <li><strong>Inference &amp; Measurement:</strong> Design and implement causal inference frameworks and statistical models to measure the impact of interventions, evaluate system performance and uncover opportunities for improvement.</li> <li><strong>Modeling:</strong> Build, evaluate and iterate on causal ML models that power high-stakes decisions, applying best practices across the full model lifecycle from feature engineering to production deployment</li> <li><strong>Optimization:</strong> Develop frameworks to analyze tradeoffs between competing objectives (accuracy, coverage, user experience and operational cost), and propose strategies to improve overall effectiveness.</li> <li><strong>Collaborate Cross-Functionally: </strong>Build strong relationships with cross-functional partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation.</li> <li><strong>Influence Decisions:</strong> Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed, data-driven decision-making.</li> <li><strong>Empowerment:</strong> Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes.</li> </ul> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>Your Expertise:</strong></span></p> <ul> <li>2+ years of industry experience in a quantitative analysis role with a Master's degree in a quantitative field (statistics, economics, computer science, etc.), or PhD in relevant fields.</li> <li>Strong knowledge of causal inference and experimental design.</li> <li>Strong knowledge of Bayesian modeling and statistical inference.</li> <li>Hands-on experience building and deploying statistical or ML models in production environments.</li> <li>Skilled in statistical programming (Python/R) and database usage (SQL).</li> <li>Proven ability to communicate clearly and effectively to audiences of varying technical levels.</li> <li>Ability to translate complex findings into compelling narratives that drive impact.</li> <li>Excellent project management, communication and collaboration skills.</li> </ul> <p><span style="color: #000000; font-family: arial, helvetica, sans-serif;"><strong>Your Location:</strong></span></p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><span style="font-weight: 400;">This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. <a style="color: #000000;" href="https://careers.airbnb.com/">Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list</a></span><span style="font-weight: 400;">. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.</span></span></p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><strong>Our Commitment To Inclusion &amp; Belonging:</strong></span></p> <p><span style="font-weight: 400; font-family: arial, helvetica, sans-serif; color: #000000;">Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.</span></p> <p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><span style="font-weight: 400;">We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: </span><a style="color: #000000;" href="mailto:reasonableaccommodations@airbnb.com"><span style="font-weight: 400;">reasonableaccommodations@airbnb.com</span></a><span style="font-weight: 400;">. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.&nbsp;</span></span></p> <p><span style="font-weight: 400; font-family: arial, helvetica, sans-serif; color: #000000;">We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.</span></p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><span style="font-size: 16px;"><strong><span style="font-family: arial, helvetica, sans-serif; color: rgb(0, 0, 0);">How We'll Take Care of You:</span></strong></span></p> <p class="p1"><span style="font-size: 16px;">Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. &nbsp;</span></p></div><div class="title">Pay Range</div><div class