Lead - Advanced Analytics, Gurgaon

Airbnb Airbnb · Consumer · Gurgaon, India · Analytics

Lead Advanced Analyst role focused on driving AI-first analytics practices within the Community Support business at Airbnb. The role involves serving as a strategic thought partner, building scalable analytical solutions, and championing the integration of LLM-based tools, AutoML, and advanced AI capabilities into analytical workflows. Responsibilities include leading product analytics, A/B testing, developing metric frameworks, and collaborating with Data Science/Engineering on ML model development for policy enforcement, while also ensuring data quality and regulatory compliance.

What you'd actually do

  1. Serve as the primary data thought partner to product and business leaders across Community Support, providing strategic insights, recommendations, and enabling data-informed decisions at an organizational level.
  2. Drive day-to-day product analytics and create scalable, reusable data tools and frameworks that elevate the entire team's analytical capability.
  3. Build and scale advanced analytical capabilities; leverage Airbnb's state-of-the-art machine learning infrastructure and central data science tools to collaborate with engineers, product managers, designers, and operations agents to achieve shared, cross-functional goals.
  4. Champion AI-first analytics practices across the team identifying high-impact opportunities to integrate LLM-based tools, AutoML, and advanced AI capabilities into analytical workflows.
  5. Lead and influence machine learning model development in partnership with DS/Engineering teams to automate policy enforcement decisions, while routing the most complex cases for manual review.

Skills

Required

  • Expert-level SQL
  • complex query optimization
  • performance tuning
  • schema design
  • ETL/ELT pipelines
  • data transformation tools
  • Advanced proficiency in Python (pandas, numpy, scikit-learn, statsmodels)
  • statistical modeling

Nice to have

  • Master's or PhD in a quantitative field
  • working knowledge of data transformation tools

What the JD emphasized

  • AI-first analytics practices
  • integrate LLM-based tools
  • AutoML
  • advanced AI capabilities
  • machine learning model development
  • regulatory compliance

Other signals

  • AI-first analytics practices
  • integrate LLM-based tools
  • AutoML
  • advanced AI capabilities into analytical workflows
  • machine learning model development
  • apply AI-assisted tools (e.g., LLMs, AutoML, NLP pipelines)