Sr. Manager, Studios Analytics, Prime Video Finance

Key job responsibilities

• Serve as the primary analytics partner to Studios Finance and Strategy leadership. Understand their most critical business questions and ensure they have timely, accurate data to inform content and portfolio decisions.
• Set organizational priorities by balancing stakeholder needs, business impact, and technical feasibility. Define the Studios analytics roadmap and ensure the team focuses on the highest-leverage work.
• Lead the design, development, and maintenance of dashboards, automated reporting, and analytical tooling that give Studios leaders real-time visibility into content performance and portfolio health.
• Drive automation of high-volume manual workflows including talent-facing presentations, slate summaries, and compliance reporting.
• Partner with centralized product development, data engineering, and financial reporting teams to influence platform roadmaps and maintain consistency with enterprise-wide data governance standards.
• Own AI integration and adoption for Studios analytics, leveraging the broader organization's AI capabilities to accelerate delivery and scale output.
• Hire, develop, and lead a high-performing team. Set technical standards, mentor team members, and build a culture of analytical rigor and customer obsession.
• Represent the analytics function in senior leadership forums, communicating insights and providing a point of view on how data should inform content strategy.

Basic Qualifications

• Knowledge of SQL and Excel
• Master's degree or above in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field, or PhD
• 10+ years of business intelligence and analytics experience
• 10+ years of delivering results managing a business intelligence or analytics team, including employee development and performance management experience

Preferred Qualifications

• Knowledge of a scripting language (Python, R, etc.)
• MBA
• Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
• Knowledge of methods for statistical inference (e.g. regression, experimental design, significance testing)
• Knowledge of large scale distributed systems (e.g., Spark, Hadoop)