Staff, Advanced Analytics, Community Support

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join: 

We are looking for an Advanced Analytics Lead to help Airbnb enable travel for our millions of guests and hosts on our platform. This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS organization.

The Difference You Will Make:

• Data thought partner to product and business leaders across teams through providing insights, recommendations, and enabling data informed decisions  
• Drive day to day analytics and create scalable data tools
• Identify pain points in traveling and hosting and work with product leadership to improve experiences for our guest, host and agent community

In addition, you will leverage Airbnb’s rich and unique data, state-of-art machine learning infrastructure, and other central data science tools to build and grow the measurement capacity within the organization. You will also be deeply involved in the technical details of the various systems we build, and will have the opportunity to collaborate with a strong team of engineers, product managers, designers and operations agents to achieve shared, cross-functional goals to help keep Airbnb’s community safe and trusted. 

• You are passionate about solving complex problems within the Community support domain with data & insights; adding a new perspective to existing solutions and making business decisions based on careful and thoughtful analysis
• You are highly proficient in building and analyzing analytical frameworks, statistical models and experimentation methods to establish and communicate causal relationships
• You are a storyteller who uses complex data and insights to frame narratives to bring others along the journey

A Typical Day: 

• Drive measurements around LLMs to determine accuracy & produce actionable insights. Setup experiments & setup end to end launch of AI assistance.
• Lead and drive data-driven roadmaps for the CS working groups. Recommend actionable solutions backed by data and metrics to product problems, with the ability to effectively communicate with Product, Operations & Engineering managers of varying technical levels
• Build the business insights & reporting platform to detect and support the driving efficacy and efficiency of  behaviors and product interfaces and processes across CS platform and contact center network 
• Perform data modeling of the various entities and using tools & frameworks for optimizing community and agent experiences 
• Defining and evaluating key metrics in an unstructured problem space including measurement of the ML models that drive product development. Communicating a robust understanding of what moves these metrics and why
• Influence data-driven decisions across business verticals in day-to-day via business reviews, scorecards, self-serve portal, OKRs and planning among others
• Influence experimentation & measurement strategies; conduct power analyses, define exit criteria, and use statistical models to improve inference. Your expertise in causal inference as well as passion for the subject matter will help you address this unstructured space

Your Expertise:

• A minimum of 10+ years of industry experience in business analytics and a degree (Masters or  PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research). 
• Have experience in ML & digital AI products - chatbot, LLMs, search & personalization expertise
• Have experience supporting community support and/or have worked closely with operations teams
• Expert skills in SQL and expert in at least one programming language for data analysis (Python or R). Experience with  non-experimental causal inference methods, experimentation and machine learning techniques,  ideally in a multi-sided platform setting
• Working knowledge of  schema design and high-dimensional data modeling (ETL framework like Airflow)
• Ability to work under conditions of ambiguity in a fast-growth, sometimes uncertain and complex environment - comfortable acting with minimal planning, direction, and supervision. You can identify issues both within and outside of your