Data Analyst, Finance

Scale Media builds and scales science-backed wellness brands and is seeking a mid-level Data Analyst, Finance. The role owns financial data accuracy, forecasting, reporting, reconciliation, and unit economics across e-commerce brands and channels. The analyst will transform transaction data, investigate discrepancies, and build dashboards to support Finance and leadership.

Responsibilities:

• Financial Forecasts: Build and maintain forecasts for revenue, orders, subscription renewals, and expenses by brand and channel, and keep them current as actuals come in
• Forecast vs. Actual: Track how forecasts compare to actuals, explain the gaps, and flag meaningful misses to the Finance team
• Budget Support: Update the scenarios and assumptions Finance uses for budget planning
• P&L Reporting: Build and maintain reporting on revenue, gross vs. net sales, discounts, refunds, COGS, and contribution margin by brand, channel, and product
• Unit Economics: Report on contribution margin, payback, and profitability by brand, channel, and product
• Month-End Close: Support month-end close with timely, tied-out data
• Budget vs. Actual: Produce variance reporting that explains what moved and why
• Reconciliation Investigations: Act as the lead investigator for revenue discrepancies. You will reconcile data between payment processors (Stripe, Shopify Payments, Amazon), bank deposits, our internal database, and accounting (QuickBooks) to ensure every dollar is accounted for
• Spend Reconciliation: Reconcile marketing spend across ad platforms and invoices against finance records
• Root Cause Fixes: Work with Finance and our Data Engineer to fix discrepancies at the source
• Metric Definitions: Document the business logic behind financial metrics so every team uses the same definitions
• Data Preparation: While we have a Data Engineer managing the infrastructure, you will handle the "last mile" of data prep using KNIME or dbt (or similar tools like Alteryx or Python/Pandas)
• Business Logic Application: Write efficient SQL to transform raw transaction data in Snowflake into usable datasets that reflect our financial business rules
• Dashboarding: Design, build, and maintain high-impact dashboards in Sigma for Finance and leadership

Requirements:

• 2–3 years of specific Data Analysis experience, ideally supporting finance
• Hands-on experience building and maintaining financial forecasts (e.g., revenue, orders, or expenses) in SQL, spreadsheets, or a BI tool
• Comfort with revenue recognition, COGS, gross vs. net sales, and contribution margin
• Proven experience in DTC E-commerce is required
• You must be comfortable with Shopify, Amazon Seller Central, and Stripe data
• Strong proficiency with Snowflake (SQL) and Sigma
• Advanced Excel or Google Sheets skills
• Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function, so you can communicate effectively with our Data Engineer
• You have built or maintained forecasts that Finance relied on, and you can explain why actuals came in above or below them
• You understand how a Shopify order becomes a processor payout and then a bank deposit, and where fees, refunds, and chargebacks create gaps
• You have the patience and precision to trace a single transaction through the entire data lifecycle to solve revenue mismatches
• You'd rather be right than fast, but you're fast too
• Competency in KNIME or dbt is preferred, but we are open to candidates experienced with Alteryx or Python who can adapt quickly
• We're open to candidates experienced with Tableau, Looker, or Power BI who can adapt quickly
• Understanding QuickBooks report structures is a plus