Senior Data Analyst, Finance

Scale Media•Burbank, CA

1d•$100,000 - $125,000•Remote

About The Position

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.

Requirements

5+ years of data or financial analytics experience, with meaningful time in DTC, subscription, or consumer businesses.
Hands-on experience with both: building financial forecasts (e.g., time-series, regression) and predictive models (e.g., logistic regression, survival analysis, gradient boosting) that leadership used to make decisions.
Strong grasp of accounting principles, and familiarity with compiling financial statements and cash flows.
Proven experience in DTC E-commerce is required.
Comfortable with Shopify, Amazon Seller Central, and Stripe data.
Expert SQL in Snowflake, strong Python (pandas, scikit-learn, statsmodels, Prophet, or similar), and proficiency with Sigma.
Advanced Excel or Google Sheets skills.
Fluency with Claude Code (or comparable AI coding tools) for data manipulation and analytics.
Awareness of how ELT tools (like Hevo, Fivetran, Airbyte, Azure, etc.) function, so you can communicate effectively with our Data Engineer.
Proven track record of designing forecasts that executive leadership relies on for strategic planning, along with the ability to articulate variance drivers and continuously calibrate model accuracy.
Know when a time-series forecast is enough and when a customer-level predictive model will do better.
Understand how a Shopify order becomes a processor payout and then a bank deposit, and where fees, refunds, and chargebacks create gaps.
Present forecasts honestly, with the assumptions and risks in plain view.
Patience and precision to trace a single transaction through the entire data lifecycle when the numbers don't add up.

Nice To Haves

Familiarity with QuickBooks report structures and month-end close is a plus.
We're open to candidates experienced with Tableau, Looker, or Power BI who can adapt quickly.

Responsibilities

Build and own forecasts for revenue, orders, subscription renewals, and cash by brand and channel.
Develop scenario and sensitivity models that help Finance plan budgets.
Track forecast accuracy over time and refine forecasts as the business changes.
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).
Feed model outputs into revenue and cash forecasts so projections reflect who is likely to renew, cancel, or refund, not just historical trends.
Monitor model performance over time and retrain as customer behavior shifts.
Own reporting on revenue, gross vs. net sales, discounts, refunds, COGS, and contribution margin by brand, channel, and product.
Own contribution margin, payback, and profitability reporting by brand, channel, and product.
Produce budget-vs-actual analysis that explains what moved and why.
Own reconciliation across payment processors (Stripe, Shopify Payments, Amazon), bank deposits, our internal database, and accounting (QuickBooks) to ensure every dollar is accounted for.
Lead investigations of revenue discrepancies and drive fixes at the source with our Data Engineer.
Define and document the business logic behind financial metrics for the whole company.
Use dbt or Python to build the financial datasets and models behind forecasting and reporting.
Write efficient SQL in Snowflake that reflects our financial business rules.
Design, build, and maintain high-impact dashboards in Sigma for Finance and executive leadership.
Present forecasts and model findings to Finance and executive leadership, including the assumptions and risks behind them.
Review other analysts' work and mentor them on financial data quality and modeling.