Data Analyst, Finance

Scale Media · United States · $80k – $100k · posted today ago

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About this role

About Scale

For the past 12 years, Scale Media has been building and scaling science-backed wellness brands. Our portfolio of brands, including Live Conscious, 1MD, and Essential Elements, has grown to 9 figures in revenue while operating profitably with no external funding.

Our team is made up of operators, marketers, and builders focused on products consumers actually trust. We're investing heavily in data and AI to sharpen how we develop products and scale brands.

We believe the best decisions come from data, curiosity, and continuous learning. We value high ownership, candid feedback, and thoughtful execution. As a fully remote company, we lead with clear communication, accountability, and trust, and we give people real room to grow and make an impact.

Scale Media has been recognized as one of Forbes' Best Startup Employers, a Great Place to Work, an Inc. Best Workplace, and an Inc. 5000 company.

If you take ownership, think for yourself, and like solving hard problems alongside people who do the same, you'll fit right in.

About the Role

We are looking for a mid-level Data Analyst who is far more than a report builder. You are a "Data Detective" who understands the heartbeat of an e-commerce P&L.

You will not just analyze data; you will own the truth behind our revenue numbers and help Finance see what's coming next. We need a Financial Data Master who understands payment processors, core financial concepts, and forecasting, and who knows how raw transaction data becomes a P&L the business can trust.

Additionally, you will act as a critical partner to our Finance team, bridging the gap between raw data, payment processors, our financial reporting, and the forecast.

What You'll Do

1. Forecasting

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.

2. Financial Reporting & Unit Economics

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.

3. Financial Data Integrity & Reconciliation

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.

4. Data Transformation & Visualization

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.

What We're Looking For

The Essentials (Experience & Tech Stack)

Experience Level: 2–3 years of specific Data Analysis experience, ideally supporting finance. (We are not looking for Junior Analysts or Senior Data Architects; we need a hands-on mid-level executor.)
Forecasting: Hands-on experience building and maintaining financial forecasts (e.g., revenue, orders, or expenses) in SQL, spreadsheets, or a BI tool. This is required.
Financial Acumen: Comfort with revenue recognition, COGS, gross vs. net sales, and contribution margin.
Industry: Proven experience in DTC E-commerce is required. You must be comfortable with Shopify, Amazon Seller Central, and Stripe data.
Warehousing & BI: Strong proficiency with Snowflake (SQL) and Sigma. We're open to candidates experienced with Tableau, Looker, or Power BI who can adapt quickly.
Spreadsheets: Advanced Excel or Google Sheets skills.
Transformation Tools: Competency in KNIME or dbt is preferred, but we are open to candidates experienced with Alteryx or Python who can adapt quickly.
ELT Familiarity: Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function, so you can communicate effectively with our Data Engineer.

The "Financial Data Master" Skill Set

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.
Understanding QuickBooks report structures is a plus.

The Financial Mindset

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.