Lead Advanced Analytics, Product

Airbnb

2h•$164,000 - $191,000•Remote

About The Position

Airbnb is seeking a Lead, Advanced Analytics to support its Host App teams. This individual will play a pivotal role in supporting strategic business and product initiatives through detailed data analysis, experimentation, statistical modeling, and the development of reporting tools and metrics. The individual will be instrumental in driving product and strategic decisions related to the Guest App.

Requirements

6+ years of industry experience with a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
Prior experience in an advanced analytics or product data science role.
Exceptional business acumen, strategic thinking skills, and the ability to conduct rigorous analysis and make informed judgments.
Excellent communication skills, capable of engaging with a variety of stakeholders and conveying complex concepts in an accessible manner.
Proven stakeholder management skills, with the ability to collaborate and influence across functions.
Experience partnering with product teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurement.
Experience in analysis of A|B experiments and statistical data analysis.
Experience designing and building metrics, from conception to building prototypes with data pipelines.
Strong expertise in at least one programming language (Python or R) and SQL.
Experience with AI-assisted analytics (Claude, ChatGPT, etc).
An agile, growth-minded approach, demonstrated through a history of driving projects from ideation to impact.

Responsibilities

Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
Apply technical expertise with quantitative analysis, experimentation, data mining, forecasting and the presentation of data to identify trends and patterns that can inform decision-making.
Collaborate closely with Product, Engineering, Finance, Marketing, Operations, Data Science, Advanced Analytics, Data and Analytical Engineering, Capacity Planning and other cross-functional teams to provide actionable insights.
Design, execute, and analyze experiments to measure feature impact and guide product iterations. Leverage causal methods when traditional randomized trials aren’t available.
Design and build metrics / dimensions to monitor product and business performance.
Build sophisticated reporting and analytical tools that empower stakeholders to make data-driven decisions.
Present findings and recommendations to stakeholders, including senior leadership, in a clear and concise manner.
Stay up-to-date with the latest industry trends and advancements in quantitative and qualitative data analysis techniques.
Leverage AI to automate repetitive tasks and empower stakeholders.