Electronic Arts

EA SPORTS is one of the most iconic brands in entertainment – connecting hundreds of millions around the world to the sports they love through a portfolio of industry-leading video games.

At the heart of EA SPORTS is the FC franchise. EA SPORTS FC is the world's #1 best-selling video game with over 200M engaged players across multiple platforms, including console, PC, and mobile. Innovation, passion, and teamwork are at the heart of everything we do. With studios in Vancouver, Bucharest, and Cologne, we're looking for the brightest talent, so we can continue to create experiences that connect with millions of hearts and minds the world over.

Your role:

As a Data Scientist, you will help us improve our FC franchise by building tools and models that help create and monitor live content. You are a technically oriented individual knowledgeable of how to use data and AI systems to solve product problems. You report to an embedded data science team in FC and will work with us, along with product managers, engineers, and technical leaders who bring EA Sports FC to life.

What a Data Scientist does at EA:

• Build data-driven applications that support designers and producers in the creation of in-game content.

• Understand how to use principles of statistics and machine learning to help learn and tune in game experiences while staying aware of their consequences.

• Draft technical solutions when presented with a problem to a less technical audience.

• Prototype new technology that fits use cases/problems and validates against success criteria.

• Support peers with technical reviews, ensuring quality coding and deployment practices.

Your Qualifications:

• BS in Mathematics, Statistics, Economics, Computer Science, or related; or equivalent experience.

• 2 or more years of experience in data science, analytics, or a related area in a consumer products-oriented industry.

• Experience developing a production-ready codebase alongside other contributors.

• Familiarity with SQL, including experience querying complex, semi-structured data sets in a data lake environment.

• Experience developing statistical and machine learning models using languages like Python or R and using tools like Sagemaker or Databricks.

• Knowledge of programming best practices, version control, and automation.

• Experience presenting to and gathering requirements from people at multiple levels of business and technical expertise.