Senior Data Analyst, Finance

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 Senior 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, and where it's headed next.

You will own the truth behind our financial numbers and how we forecast them. We need a Financial Modeling Master who can build the forecasts our Finance team plans around, plus the predictive models that make those forecasts sharper, all grounded in rigorously reconciled data.

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

1. Forecasting

• Financial Forecasts:
  Build and own forecasts for revenue, orders, subscription renewals, and cash by brand and channel.
• Scenario Planning:
  Develop scenario and sensitivity models that help Finance plan budgets.
• Forecast Accuracy:
  Track accuracy over time and refine forecasts as the business changes.

2. Predictive Modeling

• Customer & SKU-Level Models:
  Build, validate, and maintain predictive models, such as subscription renewal and cancellation likelihood, refund and chargeback risk, and SKU-level demand, using statistical and machine learning methods (e.g., logistic regression, survival analysis, gradient boosting).
• Sharper Forecasts:
  Feed model outputs into revenue and cash forecasts so projections reflect who is likely to renew, cancel, or refund, not just historical trends.
• Model Health:
  Monitor model performance over time and retrain as customer behavior shifts.

3. Financial Reporting & Unit Economics

• P&L Reporting:
  Own reporting on revenue, gross vs. net sales, discounts, refunds, COGS, and contribution margin by brand, channel, and product.
• Unit Economics:
  Own contribution margin, payback, and profitability reporting by brand, channel, and product.
• Variance Analysis:
  Produce budget-vs-actual analysis that explains what moved and why.

4. Financial Data Integrity & Reconciliation

• Reconciliation Ownership:
  Own reconciliation across payment processors (Stripe, Shopify Payments, Amazon), bank deposits, our internal database, and accounting (Quick Books) to ensure every dollar is accounted for.
• Root Cause Leadership:
  Lead investigations of revenue discrepancies and drive fixes at the source with our Data Engineer.
• Single Source of Truth:
  Define and document the business logic behind financial metrics for the whole company.

5. Data Transformation & Visualization

• Data Preparation:
  Use dbt or Python to build the financial datasets and models behind forecasting and reporting.
• Business Logic Application:
  Write efficient SQL in Snowflake that reflects our financial business rules.
• Dashboarding:
  Design, build, and maintain high-impact dashboards in Sigma for Finance and executive leadership.

6. Leadership & Collaboration

• Finance Partnership:
  Present forecasts and model findings to Finance and executive leadership, including the assumptions and risks behind them.
• Raise the Bar:
  Review other analysts' work and mentor them on financial data quality and modeling.

The Essentials (Experience & Tech Stack)

• Experience Level: 5+ years of data or financial analytics experience, with meaningful time in DTC, subscription, or consumer businesses. (We are looking for a senior, hands-on individual contributor, not a people manager.)
• Forecasting & Predictive Modeling:
  Hands-on experience with both: building financial forecasts (e.g., time-series,…