Senior Manager, Sports Analytics

This position has been filled - Job#: 453364903

Job Summary

EA Tiburon studio is looking for an Analytics Manager to drive the delivery of high-quality analysis and help studio leadership make sound business decisions about the Sports franchises.  You will solve complex problems and drive the future strategy for analytics within the studio.  You should have a strong analytics background, preferably in the area of gaming or consumer products.

Responsibilities:

• Provide strategic insights and recommendations to optimize current and future products
• Responsible for day-to-day management of analyst deliverables, including capacity planning and analysis best practices such as peer reviews, problem solving methodology, archiving, and model selection and validation techniques
• Partner with leadership to define and prioritize highest value work for the business
• Collaborate with other analytic leaders across Sports and EA to define and drive cross-franchise analytics strategy
• Manage and mentor other analysts
• Exercise judgment of appropriate methodology use for simple and complex problems
• Help shape the future analytics platform by partnering with internal technology groups to define analyst requirements

Requirements:

• Bachelor's degree. Master's/PhD preferred in Statistics, Mathematics, Economics, or related discipline
• 5+ years’ experience in quantitative analysis, preferably for a gaming or consumer products company
• 3+ years’ experience managing other team members in a formal or informal capacity
• Experience in understanding business problems and constraints, translating into analysis approach and insights, and then following through on recommendations/outcomes
• Experience leading analytical presentations to large groups and/or senior management
• Excellent project management skills to build and execute analysis delivery plans with clearly defined deliverables, timelines, ownership, and risks/issues
• In-depth and extensive knowledge of quantitative techniques and tools including the following, but not limited to, regressions, survival analysis, classification, forecasting, and clustering
• Excellent skills using statistical software, including R and Python
• Excellent SQL skills; experience with big data ecosystem such as Hive/Hadoop is a plus
• Familiarity with JIRA is a plus