Senior Staff Data Scientist, Guest & Host Marketplace AI

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:

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.

The Difference You Will Make:

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.

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 guests navigate from surface-to-surface in our app.

The ideal candidate will demonstrate to be a domain expert with granular user behavior and sequence datasets in a marketplace setting. You will hold a high bar for our customer experience and balance a passion for AI with a strong desire to accurately understand user behavior and business success. Your efforts towards personalized content discovery will help make Airbnb feel tailored for you, maintaining a dialogue with our guests to deeply understand their preferences and reflect that understanding back to them, enabling every guest to easily discover the travel they will love.

A Typical Day:

Learn: Develop deep understanding of how guests navigate and re-engage with our app via analysis, research, and by leveraging granular user action and sequence datasets.

Partner: With product and engineering, drive technical frameworks and science leadership to explore innovative paradigms for detecting revealed preferences and quantifying online frictions.

Build: Write code for prototypes to detect and quantify taxonomy of guest preferences via iterative development of data frameworks, models and artefacts derived from AI toolkits

Evaluate: Assess assumptions and efficacy of derived guest preferences via measurement and validating hypotheses linked to online guest action and engagement. Setup experiments and data feedback loops to own a high bar over continuous impact.

Influence: Regularly present findings and recommendations to leadership audiences to inform strategy and cross-functional deliverables.

If you’re passionate about going deep into personalized user experiences, we want to hear from you!

Your Expertise:

Causal inference expertise with marketplace experience

Preferred domain experience in search, UX discovery, personalized evidence systems

Advanced degree in Computer Science, Statistics, Econometrics or related field.

9+ years of industry experience with a PhD (or 12+ years with a Masters)

Strong in communication with XFN partners in product, engineering, and design to enable data-driven product development with a focus on the user experience.

Expert in at least one programming language for data analysis (Python or R) with familiarity in SQL. Comfort with developing proof-of-concept prototypes. Passionate about AI and possessing a learner’s mindset towards LLMs and dynamic systems.

Proven ability to succeed in both collaborative and independent work environments

Demonstrated willingness and track record of engagement with the technical community

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