Most Loved Workplace® Certified JobSenior Staff Data Scientist, Guest & Host Marketplace AI
Assessed by Most Loved Workplace®About the Role
At Airbnb, a Most Loved Workplace® certified employer in the Travel & Hospitality space, Belong Anywhere: Connect Through Travel, Community, and Trust.
<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><strong>The Community You Will Join:</strong></p>
<p>Guest Experience is responsible for Search and Discovery, Merchandising, and end-to-end online software experience worldwide from top-of-funnel discovery through post-booking engagement. We are looking for a talented Data Scientist to join the Guest Data Science team. This tech lead will be at the core of using AI and casual inference to understand user behavior in our app, detect underlying intent, and to build data products needed to provide a compelling and personalized experience of our app. We build products that help guests find the inventory most relevant to them in our marketplace.<br><br></p>
<p><strong>The Difference You Will Make:</strong></p>
<p>As a Senior Staff Data Scientist, you will lead innovation efforts to build methodologies to identify and evaluate the preferences important to every guest, at every step of their online discovery funnel. You will be instrumental in shaping our data strategy to drive guest conversion and regular engagement with the Airbnb platform across our Homes, Experiences and Services business verticals.&nbsp;</p>
<p>This role emphasizes technical excellence and driving business impact with cutting-edge science. Your role will involve close collaboration with Product to identify in-product optimizations and shape UX design architecture to path how gu
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