Electronic Arts

We evolve our games and how players interact with them by leveraging the power of data to continuously uncover insights to deliver an even better player experience. We strive to be the best-in-class AI team in the gaming industry by maximizing the fun for EA players through easier deployment of AI-driven solutions for game makers. Our insights are ubiquitous through autonomous analytics.

As a Sr Data Analyst in the EA Data & Analytics group, you will play a pivotal role in shaping the future of our mobile sports titles, including Madden Mobile and an innovative new basketball game in development. You will collaborate with development and business teams, reporting directly to a Senior Analytics Manager. You will work closely with developers to launch and refine new titles, while driving growth and engagement for our established games.  You will become an integral member of the Sports Analytics team, enhancing our analytics capabilities for both current and future mobile experiences.

Responsibilities:

• You will report to a Senior Manager under the Director of Sports Analytics for the Tiburon Studio.

• You will Collaborate with our Live Service team to establish key metrics and targets to measure program and content performance against expectations.

• You will receive questions from our partners, determine how our data can help answer them, and provide insights through reports, presentations, or dashboards.

• You will lead presentations to diverse audiences including senior management.

• You will help to shape and implement analytics best practices and our team vision

Qualifications:

• A degree in a quantitative discipline (Analytics, Data Science, Business, Statistics, Mathematics, Economics)

• 3+ years of experience in an analytics role performing quantitative analysis with big data to help guide decisions.           

• 1+ years of experience independently managing projects and building analysis plans with clear goals & timelines.         

• Expertise in SQL and ability to extract data from large data sources with differing structures.   

• Proficiency analyzing large datasets in programmatic analysis tools (e.g. Python, R)

• Experience with data visualization software (e.g. Tableau, PowerBI, Looker).

• Experience in statistical modeling (e.g. regression, clustering, predictive modeling).