Responsibilities

• Analyze revenue and performance data across channels, funnels, and accounts to establish what drove growth, what didn’t, and what it cost
• Build unit economics views (CAC, LTV, payback period, margin, ROAS) and flag where spend stops earning its keep
• Build dashboards and reports in Looker Studio, Sheets, Excel, or similar that executives can read without a guided tour
• Run cohort, funnel, and attribution analysis, and QA tracking and data integrity across ad platforms, analytics, and CRM
• Support forecasting and budget allocation models: scenarios, sensitivities, and what-if cases
• Evaluate test results and say whether the lift is real or just noise
• Clean and reconcile messy data from multiple sources
• Write up findings as concise, client-ready summaries that lead with a recommendation, not a data dump
• Put AI tools to work in analysis and reporting, and verify before trusting

Requirements

• Graduate student (MBA, MS in finance, analytics, or similar) preferred, or in your final year of undergrad
• Demonstrated analytical work through internships, coursework, or projects in business, finance, economics, or marketing analytics
• Strong spreadsheet skills (pivots, lookups, modeling); SQL a plus; familiarity with a BI tool (Looker Studio, Tableau, Power BI) a plus
• Working grasp of business metrics: revenue, margin, conversion, CAC, LTV, ROAS
• Statistical common sense: you know signal from noise and correlation from causation
• Able to turn data into plain-English conclusions at a high standard of business communication
• A critical thinker who does not accept "the dashboard says so" as an argument
• Meticulous. One bad join can turn a tidy chart into a confident lie
• Commercially minded: you ask what it costs and what it returns before you ask what it looks like
• Curious, self-directed, and motivated. We don't manage calendars

Preferred

• SQL a plus; familiarity with a BI tool (Looker Studio, Tableau, Power BI) a plus