Ecommerce Data Analyst – Build Automated Sales, Refund, Dispute & COGS Dashboard

Overview We are a fast-growing U.S.-based ecommerce brand looking for an experienced Ecommerce Data Analyst to build a robust dashboard that tracks: - Sales, Refunds, Disputes, COGS breakdown by SKU - Daily profitability - Time-based trends - Cohort analysis and trends This is NOT basic spreadsheet cleanup. We need someone who understands ecommerce metrics and profitability analysis. Project Scope You will: Consolidate data from: Stripe (payments, refunds, disputes) Dispute management platform Order management system COGS data Build a clean data model that: Identifies repeating vs new orders Calculates lost COGS on fulfilled disputed transactions Calculates refund rate by cohort Calculates dispute rate by cohort Create an automated dashboard that shows: Revenue by SKU Gross margin by SKU Refund rate trends Dispute rate trends Cohort performance (weekly and monthly) LTV vs refund/dispute risk (if possible) Required Experience You must have experience with: Ecommerce analytics Stripe data Cohort analysis Refund / chargeback analysis Unit economics modeling Advanced Excel or Google Sheets (required) Bonus: SQL, Looker Studio, Power BI Please include examples of dashboards you’ve built for ecommerce businesses. Important To apply, answer the following: How would you match Stripe disputes to internal order records? How would you calculate true margin after refunds and disputes? Have you built cohort analysis before? Briefly explain your method. What tools would you recommend for scalability? Generic proposals will not be considered. Ideal Candidate Thinks in terms of unit economics, not just revenue Has worked with ecommerce brands Understands chargeback impact on cash flow Can suggest KPI improvements Proactive, not just task-following Apply tot his job

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