Airbnb
Senior Staff Data Scientist, Guest & Host Marketplace AI
Remote Data Science role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalLead
Work settingRemote
Accepted candidate locations
USA
Role overview
Senior Staff Data Scientist, Guest & Host Marketplace AI
Requirements and responsibilities
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Details
- 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!
- 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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