Senior Analyst, Advanced Analytics - Gurugram

Airbnb Airbnb · Consumer · Bangalore, India · Analytics

Senior Analyst role focused on building agentic analytics pipelines and intelligent interfaces for the Community Support organization at Airbnb. The role involves automating insight generation, developing reusable agent tools, designing prompt templates, building orchestration workflows, deploying self-serve interfaces, and creating evaluation/observability frameworks. The goal is to make AI-powered analytics accessible, trusted, and actionable, enabling self-serve capabilities within CS.

What you'd actually do

  1. Build agentic analytics pipelines that automate insight generation across all key metrics including contact volume, handle time, and resolution quality — reducing analytical drag across CS.
  2. Develop reusable skill libraries — composable agent tools (volume lookups, NPS pulls, handle time calculations) callable across workflows and teams.
  3. Design and govern prompt templates and playbooks — standardised, governed prompts for recurring analytical questions (e.g. “what drove contact volume this week”).
  4. Build orchestration workflows — multi-step pipelines that chain skills together to produce automated insight narratives and proactive alerts without manual intervention.
  5. Deploy self-serve interfaces that enable non-technical personas to query certified data independently.

Skills

Required

  • Advanced SQL
  • Advanced Python at production-grade standard
  • experience on large-scale data systems (Presto, Hive, etc.)
  • experience in analytics/data science with a strong track record of solving ambiguous business problems and driving measurable impact
  • Proven ability to own end-to-end data projects — from problem scoping and data extraction to analysis, insight generation (including BI tools), and business recommendations

Nice to have

  • AI Vision Multiplier for the CS organisation
  • functional expertise in building analytical solutions
  • trusted partner to business teams and leaders
  • providing insights, recommendations, and enabling data driven decisions
  • support Business leaders within our Community Support organization
  • partner directly with functions and operational leaders across Community Support
  • making CS smarter and faster
  • enable self-serve through data
  • dedicated AI practitioner
  • building agentic solutions and intelligent interfaces
  • elevate the entire organisation toward self-serve
  • reusable skill libraries
  • composable agent tools
  • prompt templates and playbooks
  • orchestration workflows
  • multi-step pipelines
  • self-serve interfaces
  • non-technical personas to query certified data independently
  • prompt-driven dashboards
  • Automate business reviews
  • evaluation and observability frameworks
  • monitor agent output quality
  • detect drift
  • ensure outputs stay within governed data boundaries
  • Define, document, and certify metrics
  • drive the analytics roadmap, prioritization, and delivery of solutions
  • Execute projects with regular direction
  • providing constant updates to business stakeholders, analytics management
  • deliver against agreed timelines
  • translate ambiguous business problems into agentic or automated analytical solutions
  • independently scoping, building, and iterating end to end
  • Prototype and ship prompt-driven dashboards and apps
  • compressing the cycle from question to live view for varied CS personas
  • Build and iterate on skill libraries and orchestration workflows
  • expanding the reusable agent toolkit
  • Monitor agent output quality via observability frameworks
  • identifying drift or hallucinations
  • maintaining governance standards
  • Engage directly with key stakeholders to prioritise the self-serve and automation needs
  • setting and delivering against a quarterly roadmap
  • Stay at the forefront of applied AI developments
  • evaluating new tools and frameworks for relevance to CS use cases
  • embedding them rapidly into workflows
  • Ensure the availability of data quality and integrity for analysis and reporting
  • blending external and internal data sources
  • working closely with global operations and India analytics functions

What the JD emphasized

  • AI Vision Multiplier
  • builder-analyst
  • internal AI capabilities into working solutions
  • AI-powered analytics accessible, trusted, and actionable
  • building agentic solutions and intelligent interfaces
  • ship AI-enabled solutions, not just analyses
  • own end-to-end data projects
  • monitor agent output quality
  • detect drift
  • ensure outputs stay within governed data boundaries

Other signals

  • AI Vision Multiplier
  • AI-powered analytics accessible, trusted, and actionable
  • building agentic solutions and intelligent interfaces
  • automate insight generation
  • reusable skill libraries
  • composable agent tools
  • orchestration workflows
  • multi-step pipelines
  • self-serve interfaces
  • prompt-driven dashboards
  • Automate business reviews
  • evaluation and observability frameworks
  • monitor agent output quality
  • detect drift
  • ensure outputs stay within governed data boundaries
  • applied AI developments