Senior Staff Data Scientist, Guest & Host Marketplace AI

Airbnb Airbnb · Consumer · United States · Data Science

Senior Staff Data Scientist to join the Guest Data Science team, focusing on using AI and causal inference to understand user behavior, detect intent, and build data products for a personalized guest experience. The role involves leading innovation, shaping data strategy, and collaborating with Product to optimize in-product experiences and UX design. Responsibilities include analyzing user behavior, developing technical frameworks, building prototypes with AI toolkits, evaluating preferences, and influencing strategy through presentations. Requires expertise in causal inference, marketplace experience, advanced degree, and strong programming skills in Python/R and SQL.

What you'd actually do

  1. 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.
  2. With product and engineering, drive technical frameworks and science leadership to explore innovative paradigms for detecting revealed preferences and quantifying online frictions.
  3. 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
  4. 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.
  5. Regularly present findings and recommendations to leadership audiences to inform strategy and cross-functional deliverables.

Skills

Required

  • Causal inference expertise
  • marketplace experience
  • Python or R
  • SQL
  • developing proof-of-concept prototypes
  • advanced degree in Computer Science, Statistics, Econometrics or related field
  • 9+ years of industry experience with a PhD (or 12+ years with a Masters)

Nice to have

  • domain experience in search, UX discovery, personalized evidence systems
  • familiarity in SQL
  • learner’s mindset towards LLMs and dynamic systems

What the JD emphasized

  • Causal inference expertise with marketplace experience
  • domain expert with granular user behavior and sequence datasets in a marketplace setting
  • hold a high bar for our customer experience
  • accurately understand user behavior and business success
  • deeply understand their preferences

Other signals

  • building data products
  • understanding user behavior
  • personalized experience
  • guest conversion
  • guest engagement
  • identify and evaluate preferences
  • quantifying online frictions
  • detecting revealed preferences
  • personalized content discovery