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Sr. Lead Data Analyst (Merchandising and Revenue)

Poshmark · US California (Redwood City) - Office

RemoteSeniorData and MLAll DepartmentsRevenue Data Analytics TeamPosted 2 months ago
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About this role

ABOUT POSHMARK Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury. ABOUT THE ROLE We are seeking a highly motivated and experienced Sr. Lead Data Analyst to join our Analytics team. This pivotal role will serve as the analytical powerhouse for two of our most critical domains: Merchandising and Revenue. You will lead data strategy, define KPIs, and deliver actionable insights that drive product innovation, optimize the live shopping experience, and enhance merchandising strategies to maximize buyer engagement and seller success. KEY RESPONSIBILITIES - Strategic Partnership: Act as the primary data partner for Product, Engineering, and Business leaders across both the Revenue and Merchandising organizations. - Full-Cycle Analytics: Lead end-to-end analytics initiatives, from defining metrics and building foundational dashboards to conducting complex, deep-dive analyses that inform strategic decisions. - AI-Empowered Productivity: Meaningfully integrate Generative AI tools (e.g., Gemini, Claude, ChatGPT) into your daily workflows to accelerate SQL/Python code generation, automate routine analytics tasks, and enhance overall output efficiency. - Experimentation & Causal Inference: Design, execute, and analyze A/B tests and quasi-experiments to evaluate the impact of new features, algorithms, and merchandising campaigns. - Live Shopping Optimization (Shows): Analyze viewer engagement, host performance, auction dynamics, and conversion fu

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