Director, Data Analytics

PoshmarkRedwood City, CA

About The Position

Poshmark is seeking a proactive, commercially driven Director of Data Analytics to join the Revenue team. This role is the analytical engine behind Poshmark's merchandising, growth, and supply strategy, responsible for building the intelligence infrastructure that tells us what buyers want, where supply is failing to meet demand, and where seller GMV opportunity is being left on the table. The ideal candidate doesn't wait to be asked. They see the opportunity in the data before anyone else does, know exactly which signals to pull and how to connect them, and build the dashboards, frameworks, and tools that turn raw platform data into decisions the business can act on in real time. This is a builder role. You will define the data architecture for how the Revenue team operates, from inventory health and sell-through reporting to trend cycle intelligence, supply gap identification, and seller GMV opportunity and partner directly with the CRO and cross-functional leads across Merchandising, Growth Marketing, Supply Partnerships, Product, and Data Engineering.

Requirements

  • 8–12 years in data analytics, with meaningful time spent in consumer marketplace, e-commerce, fashion, or retail environments.
  • Proven track record of building analytics infrastructure that changed how a business makes decisions not just reported on decisions already made.
  • Experience working directly with senior commercial leadership and translating business strategy into data architecture.
  • Demonstrated experience leading or growing a team of analysts; strong senior individual contributors will be considered for the right candidate.
  • Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.
  • Expert-level proficiency in SQL. Strong programming skills in Python for data manipulation, statistical analysis, and pipeline automation.
  • Hands-on experience in Databricks, Snowflake, or equivalent large-scale data environments.
  • Experience with dbt or similar data transformation frameworks and modern data stack tooling.
  • Advanced dashboard and visualization skills proficient in Looker, Tableau, or equivalent; knows the difference between a report and a decision surface.
  • Familiarity with behavioral event data, funnel analytics, and supply/demand modeling in a two-sided marketplace context.
  • Practical, hands-on experience using LLMs (e.g., Claude, Gemini, ChatGPT) to write and optimize queries, troubleshoot code, and accelerate analytics workflows.
  • Commercial instincts to match technical fluency understands how sell-through rate, inventory liquidity, trend velocity, and supply gaps connect to revenue outcomes.
  • Proven ability to translate complex data into actionable business recommendations and communicate effectively with non-technical stakeholders.
  • Strong project management skills; able to manage multiple workstreams across cross-functional partners simultaneously.
  • Ability to tell a story with data and drive executive alignment on analytical findings and infrastructure investment.

Nice To Haves

  • Experience with two-sided marketplace data (supply and demand dynamics, inventory liquidity modeling).
  • Background in fashion, resale, or consumer lifestyle platforms.
  • Familiarity with CDPs Segment, mParticle, Hightouch, or Salesforce and behavioral event data pipelines.
  • Experience building or integrating AI/LLM-powered analytics systems or data products.
  • Exposure to paid media performance analytics across Meta, Google, TikTok, and Pinterest.
  • Background in demand forecasting, inventory planning, or assortment analytics.
  • Experience developing or maintaining data governance standards and documentation.
  • Deep understanding of A/B testing methodologies, statistical significance, and causal inference techniques.

Responsibilities

  • Build the Revenue Intelligence Infrastructure. Own the end-to-end analytics stack for the Revenue team, defining what data we need, how it connects, and how it surfaces as a single source of truth across demand signals, inventory health, sell-through, and seller GMV opportunity.
  • Own Demand & Supply Intelligence. Translate search acceleration, save behavior, sell-through rates, and category liquidity into a live picture of platform health. Identify where supply is failing to meet demand and build the framework that matches buyer intent to seller opportunity.
  • Drive Trend & Supply Gap Intelligence. Build continuous systems that surface which trends are accelerating, where supply gaps are forming, and where early sourcing is needed, packaging these into actionable briefs that let Supply Partnerships and Merchandising move before a GMV window closes.
  • Create Decision Surfaces, Not Reports. Build operational dashboards for the CRO and Revenue leadership that answer specific business questions daily, and own their ongoing quality, accuracy, and evolution.
  • Lead AI-Powered Analytics. Integrate GenAI tools into daily workflows to accelerate output, and architect toward a Revenue Intelligence Platform where demand sensing, campaign performance, and seller opportunity are surfaced automatically and continuously.
  • Partner Cross-Functionally & Build the Team. Serve as the analytical backbone for Merchandising, Growth, Supply Partnerships, and Product. Partner with Data Engineering to productionize frameworks. Hire, mentor, and grow a team of analysts and promote a data-driven culture across the Revenue org.
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