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
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