Senior Analyst, Advanced Analytics

The Analytics Centre of Excellence (ACOE) at Airbnb, based in India, is a hub of knowledge and expertise that aims to provide data-driven decision-making, enabling Airbnb's business goals. The ACOE's vision is to build a world-class analytics organization that provides scalable analytics. We work with various business functions such as payments, trust, digital, customer support, hosting, sales, social, compliance, risk, platforms and partnership & economics.

The ACOE's delivery framework is designed to provide relevant and contextual insights for data-driven decisions. This includes a one-stop solution for metrics, dashboards driving actionable insights, optimization of performance, measuring pre/post feature impact, sizing the ROI of opportunities, prioritization of opportunities, anomaly-driven alerting mechanisms, root cause analysis of metric deviation, and exploratory hypothesis testing.

The Community You Will Join:

We are looking for a Senior Analyst to serve as an AI Vision Multiplier for the CS organisation - a builder-analyst with a clear mandate to translate Airbnb's internal AI capabilities into working solutions that make AI-powered analytics accessible, trusted, and actionable across CS. The analyst must have functional expertise in building analytical solutions and be a trusted partner to business teams and leaders, through providing insights, recommendations, and enabling data driven decisions. This role will sit under the Advanced Analytics family and support business leaders within our Community Support organization. You will partner directly with functions and operational leaders across Community Support. This role will be responsible for making CS smarter and faster, and enable self-serve through data. You will be the team's dedicated AI practitioner, building agentic solutions and intelligent interfaces that elevate the entire organisation toward self-serve.

The Difference You Will Make:

• 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.
• Develop reusable skill libraries - composable agent tools (volume lookups, NPS pulls, handle time calculations) callable across workflows and teams.
• Design and govern prompt templates and playbooks - standardised, governed prompts for recurring analytical questions (e.g. "what drove contact volume this week").
• Build orchestration workflows - multi-step pipelines that chain skills together to produce automated insight narratives and proactive alerts without manual intervention.
• Deploy self-serve interfaces that enable non-technical personas to query certified data independently.
• Ship rapid, prompt-driven dashboards that compress the cycle from business question to live view, serving varied personas without analyst bottleneck.
• Automate business reviews - scheduled, agent-generated summaries of key CS metrics delivered to stakeholders without manual effort.
• Build and maintain evaluation and observability frameworks that monitor agent output quality, detect drift, and ensure outputs stay within governed data boundaries.
• Define, document, and certify metrics within Minerva 2.0 and Midas, ensuring agentic outputs and self-serve interfaces are anchored to a single source of truth across CS.

A Typical Day:

• Drive the analytics roadmap, prioritization, and delivery of solutions in up to a quarter ahead. Execute projects with regular direction providing constant updates to business stakeholders, analytics management and deliver against agreed timelines.
• Partner with CS operational leaders to 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 available to the CS Analytics team.
• Monitor agent output quality via observability frameworks, identifying drift or hallucinations and 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 and embedding them rapidly into workflows.
• Ensure the availability of data quality and integrity for analysis and reporting by blending external and internal data sources, working closely with global operations and India analytics functions.

Your Expertise:

• 5+ years of experience in analytics/data science with a strong track record of solving ambiguous business problems and driving measurable impact, shipping AI-enabled solutions, not just analyses.
• 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.
• Advanced SQL and Python at production-grade standard, with experience on large-scale data systems (Presto, Hive, Spark).
• Rapid front-end prototyping - vibe-coded dashboards, apps, or embedded analytics built at speed for non-technical audiences.
• Advanced Tableau proficiency for certified, production-grade BI delivery.
• Metrics governance and certification - ability to define, document, and certify metrics, ensuring agentic outputs are anchored to a single source of truth.
• Production LLM and prompt engineering experience - shipped LLM-integrated workflows, governed prompt libraries, and retrieval-based systems.
• Agentic system and orchestration design - tool chaining, context management, and building reliable pipelines with minimal human-in-the-loop intervention.
• RAG, vector databases, and semantic search - applied to unstructured contact and case data.
• Agent output evaluation and observability - experience monitoring AI pipeline quality and maintaining governance guardrails.
• Strong communication skills with the ability to translate complex AI-powered solutions into clear narratives for non-technical business stakeholders.
• Self-starter mindset with high ownership, comfortable operating with quarterly autonomy in a fast-paced environment.