Programmatic Revenue Analyst

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How Will You Grow

• Own end-to-end monthly revenue reconciliation process across all programmatic offerings using Datorama (Marketing Cloud Intelligence)
• Ingest, clean, and normalize usage reports from multiple activation platforms, including DMPs (Liveramp, Semasio), SSPs (Magnite, Freewheel, OpenX, Xandr Curate, Pubmatic), CTV AdServers (Springserve), and DSPs (The Trade Desk, Xandr Curate, DV360)
• Map all programmatic product usage data to Salesforce Opportunities and Product Line Items to ensure accurate revenue attribution
• Build and maintain comprehensive dashboards that provide visibility into programmatic revenue streams
• Analyze and validate impression data, CPMs, Traffic Acquisition Costs (TAC), and revenue share agreements across different usage reports 
• Proactively investigate and resolve revenue discrepancies between platform usage reports and Salesforce opportunities to maintain data integrity and accurate forecasting
• Drive cross-functional alignment between Finance, Sales, and Operations teams to ensure timely and accurate revenue recognition, reporting, and billing processes
• Analyze platform performance metrics to deliver actionable revenue insights and growth opportunities to key stakeholders across Sales, Finance, and Executive teams
• Lead process automation initiatives and develop strategic recommendations for new tools and technologies to optimize the monthly reconciliation workflow.

Requirements

• 5+ years of experience in programmatic advertising, adtech, or data analysis 
• Degree in Business Analytics, Data Science, Computer Science, or related field
• Deep understanding of programmatic advertising metrics (impressions, CPMs, revenue shares) and usage reports across DMPs, SSPs, DSPs, and ad servers
• Advanced Excel and Google Sheets experience with experience writing scripts
• Experience with tools like Datorama(Marketing Cloud Intelligence) Tableau, or Looker
• Proficiency in Salesforce CRM and ability to understand complex data relationships
• Meticulous attention to detail and ability to investigate data anomalies
• Excellent problem-solving skills with the ability to work independently
• Strong communication skills to effectively collaborate with cross-functional teams

Preferred Qualifications

• Experience with Python (Pandas) or R for data analysis and automation
• SQL proficiency for querying and analyzing large datasets
• Knowledge of APIs and data integration concepts
• Experience with version control systems like Git
• Experience with ETL processes and data warehousing concepts