About the Company
Scale Media builds and grows science-backed wellness brands, including Live Conscious, 1MD, and Essential Elements. Over the past 12 years, its portfolio has grown to nine-figure revenue while remaining profitable without external funding.
The company brings together operators, marketers, and builders focused on developing trusted consumer products. It invests in data and AI to improve product development and brand growth. Scale Media operates as a fully remote company and values ownership, clear communication, accountability, candid feedback, and continuous learning. Its recognition includes Forbes' Best Startup Employers, Great Place to Work, an Inc. Best Workplace, and the Inc. 5000.
About the Role
Scale Media is seeking a mid-level Data Analyst to support financial reporting, forecasting, and data integrity across its direct-to-consumer (DTC) e-commerce brands.
This role goes beyond routine reporting. You will work closely with the Finance team to understand revenue performance, maintain financial forecasts, investigate transaction discrepancies, and ensure financial reports reflect accurate and consistent data.
You will connect information from e-commerce platforms, payment processors, bank deposits, and accounting systems to help the business understand its financial performance and make informed decisions. The role also involves transforming raw data in Snowflake and developing dashboards for Finance and leadership.
Key Responsibilities
•Build and maintain forecasts for revenue, orders, subscription renewals, and expenses by brand and channel.
•Compare forecasts with actual results, explain variances, and flag significant differences to the Finance team.
•Update forecasting scenarios and assumptions to support budget planning.
•Develop and maintain profit and loss (P&L) reporting covering revenue, gross and net sales, discounts, refunds, cost of goods sold (COGS), and contribution margin.
•Analyze unit economics, payback, and profitability across brands, channels, and products.
•Support month-end close by providing timely, reconciled financial data.
•Prepare budget-versus-actual reports and explain the factors driving financial changes.
•Investigate revenue discrepancies by reconciling data from Stripe, Shopify Payments, Amazon, bank deposits, internal databases, and QuickBooks.
•Reconcile marketing expenses across advertising platforms, invoices, and finance records.
•Work with Finance and the Data Engineer to identify root causes and resolve data discrepancies at their source.
•Document financial metric definitions and business logic to maintain consistency across teams.
•Prepare and transform data using KNIME, dbt, or comparable tools such as Alteryx or Python/Pandas.
•Write efficient SQL queries to transform raw transaction data in Snowflake into datasets that follow the company's financial rules.
•Design, build, and maintain dashboards in Sigma for Finance and leadership.
•Work with the Data Engineer to understand data integration processes and improve the reliability of financial reporting.
Required Qualifications
•Two to three years of data analysis experience, ideally supporting Finance.
•Hands-on experience building and maintaining financial forecasts for revenue, orders, expenses, or similar business metrics.
•Understanding of revenue recognition, COGS, gross and net sales, and contribution margin.
•Professional experience in direct-to-consumer (DTC) e-commerce.
•Familiarity with Shopify, Amazon Seller Central, and Stripe data.
•Strong SQL skills and experience working with Snowflake.
•Advanced proficiency in Excel or Google Sheets.
•Experience building and maintaining BI dashboards, preferably in Sigma. Experience with Tableau, Looker, or Power BI is also relevant.
•Ability to investigate financial discrepancies, trace transactions across systems, and explain differences between reported and actual results.
•Strong analytical skills, attention to detail, and the ability to communicate findings clearly.
Preferred Qualifications
•Experience with KNIME or dbt for data preparation and transformation.
•Experience with Alteryx or Python/Pandas and the ability to adapt to comparable transformation tools.
•Familiarity with ELT tools such as Hevo, Fivetran, Airbyte, or Azure data services.
•Understanding of QuickBooks reporting structures.
•Experience reconciling e-commerce orders, payment processor payouts, bank deposits, fees, refunds, and chargebacks.
Salary & Benefits
•Salary: $80,000–$100,000, depending on experience.
•Employment type: Full-time.
•Work arrangement: Fully remote.
•Medical, dental, vision, and life insurance.
•Monthly work-from-home stipend.
•Paid time off program.
•Discounts on company products.
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