Sr. Lead Data Analyst (Shows & Merchandising)

Poshmark•Redwood City, CA

About The Position

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: Posh Shows (our live shopping experience) and Marketplace Merchandising. 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.

Requirements

7+ years of experience in Data Analytics, Data Science, or a related field, with a strong preference for experience in e-commerce, marketplaces, or live streaming.
Expert-level proficiency in SQL.
Strong programming skills in Python or R for data manipulation and statistical analysis.
Practical, hands-on experience using LLMs (e.g., Gemini, ChatGPT, Claude) to write and optimize queries, troubleshoot code, and perform analytics tasks with high efficiency and productivity.
Advanced experience with BI tools such as Tableau, Looker, or similar platforms.
Deep understanding of A/B testing methodologies, statistical significance, and causal inference techniques.
Proven ability to translate complex data into actionable business recommendations and communicate effectively with non-technical stakeholders.
Demonstrated experience leading cross-functional projects and mentoring peers.
Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.

Responsibilities

Act as the primary data partner for Product, Engineering, and Business leaders across both the Shows and Merchandising organizations.
Lead end-to-end analytics initiatives, from defining metrics and building foundational dashboards to conducting complex, deep-dive analyses that inform strategic decisions.
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.
Design, execute, and analyze A/B tests and quasi-experiments to evaluate the impact of new features, algorithms, and merchandising campaigns.
Analyze viewer engagement, host performance, auction dynamics, and conversion funnels to optimize the Posh Shows ecosystem.
Analyze supply and demand trends, search & discovery performance, and personalized recommendations to improve inventory liquidity and user engagement.
Mentor junior data analysts, elevate the team's technical rigor, and promote a data-driven culture across the company.
Build and maintain scalable data models and intuitive, automated dashboards (e.g., using Looker or Tableau).