Own high-impact revenue strategy analyses from problem framing through recommendations and decision support. Analyze marketplace performance, lead economics, monetization, retention, product adoption, and operating models using SQL, Python, financial modeling, and cross-functional data. Advise senior leaders, create executive- and board-ready materials, improve metric reliability, build reusable analytical frameworks, and influence decisions across Revenue, Product, Finance, and Operations.

Conduct exploratory and hypothesis-driven analysis across disparate data sources to identify business opportunities, risks, and causal relationships. Build metrics, reports, and dashboards to monitor performance and experiments, while partnering with decision-makers to communicate insights and improve data-driven decisions. Contribute to data structure modernization, modeling, and ETL initiatives while managing multiple analytical projects.

Lead product analytics for the Dealer team: run exploratory analyses, build and audit metrics, create dashboards, automate data transformations (dbt/LookML), partner with Data Engineering, and present insights to influence product strategy. Use SQL, Python/R, and GenAI tools to solve complex data problems and improve product performance.