Data Analyst, Finance

Scale Media•Burbank, CA

1d•$80,000 - $100,000•Remote

About The Position

Scale Media is seeking a mid-level Data Analyst to join their Finance team. This role is described as a "Data Detective" who understands the heartbeat of an e-commerce P&L. The analyst will be responsible for owning the truth behind revenue numbers, assisting Finance with future projections, and acting as a critical partner to bridge the gap between raw data, payment processors, financial reporting, and forecasting. The company emphasizes data-driven decisions, curiosity, continuous learning, high ownership, candid feedback, and thoughtful execution. Scale Media is a fully remote company that has been recognized for its workplace culture and growth.

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.
Comfort with Shopify, Amazon Seller Central, and Stripe data.
Strong proficiency with Snowflake (SQL) and Sigma.
Advanced Excel or Google Sheets skills.
Competency in KNIME or dbt is preferred, but candidates experienced with Alteryx or Python who can adapt quickly are open.
Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function.
Experience building or maintaining forecasts that Finance relied on, and ability to explain forecast vs. actual variances.
Understanding of how a Shopify order becomes a processor payout and then a bank deposit, including fees, refunds, and chargebacks.
Patience and precision to trace a single transaction through the entire data lifecycle to solve revenue mismatches.
Ability to be right and fast.

Nice To Haves

Understanding QuickBooks report structures is a plus.
Experience with Tableau, Looker, or Power BI who can adapt quickly.
Experience with Alteryx or Python who can adapt quickly.

Responsibilities

Build and maintain forecasts for revenue, orders, subscription renewals, and expenses by brand and channel, updating them as actuals come in.
Track forecast vs. actual performance, explain discrepancies, and flag significant misses to the Finance team.
Update scenarios and assumptions used by Finance for budget planning.
Build and maintain reporting on revenue, gross vs. net sales, discounts, refunds, COGS, and contribution margin by brand, channel, and product.
Report on unit economics, including contribution margin, payback, and profitability by brand, channel, and product.
Support month-end close with timely and accurate data.
Produce variance reporting comparing budget vs. actuals, explaining the reasons for changes.
Act as the lead investigator for revenue discrepancies, reconciling data between payment processors (Stripe, Shopify Payments, Amazon), bank deposits, internal databases, and accounting (QuickBooks).
Reconcile marketing spend across ad platforms and invoices against finance records.
Collaborate with Finance and the Data Engineer to fix discrepancies at their source.
Document the business logic behind financial metrics to ensure consistent definitions across teams.
Perform the "last mile" of data preparation using tools like KNIME or dbt.
Write efficient SQL to transform raw transaction data in Snowflake into usable datasets reflecting financial business rules.
Design, build, and maintain dashboards in Sigma for Finance and leadership.