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

reputed company We are a fast-growing U.S.-based ecommerce brand looking for an reputed company 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: reputed company (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 reputed company by cohort Calculates dispute reputed company by cohort Create an automated dashboard that shows: reputed company by SKU Gross margin by SKU Refund reputed company trends Dispute reputed company trends Cohort performance (weekly and monthly) LTV vs refund/dispute risk (if possible) Required Experience You must have experience with: Ecommerce analytics reputed company data Cohort analysis Refund / chargeback analysis Unit economics modeling Advanced reputed company or reputed company Sheets (required) Bonus: SQL, Looker Studio, Power BI Please include examples of dashboards you’ve reputed company for ecommerce businesses. Important To apply, answer the following: How would you match reputed company disputes to internal order records? How would you calculate true margin after refunds and disputes? Have you reputed company cohort analysis before? reputed company 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 reputed company Has worked with ecommerce brands Understands chargeback reputed company on cash reputed company Can suggest KPI improvements Proactive, not just task-following Apply tot his job Apply To this Job