Data Science Intern

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.

EADP EA’s Digital Platform (EADP) organization is responsible for driving critical technology decisions and investments for EA on a global scale, across all divisions and studio teams. Technology and engineering leadership at EA is critical to making the industry’s best games & services and the EADP team is leading the way to providing cross-platform services that will keep our consumers connected with our games anytime, anywhere with anyone.

As a Data science intern, you will get hands-on experience of developing custom machine learning models to tackle real-world challenges within EA's games. EA’s network of games caters to tens of millions of monthly active users. You'll have the opportunity to build solutions that can scale at real time to handle several thousand requests per second and driving the player engagement of many of the industry’s most popular titles.

If you like solving complex computing problems, are a passionate team player and thrive in a fast paced, ever changing development environment this is a great opportunity for you. Location

• Hyderabad Responsibilities Work with Product Managers, senior engineers and peers to understand requirements, prototype & build large scale distributed applications Develop and implement custom machine learning models Clean, preprocess, and analyze large datasets, ensuring data quality and integrity. Address and manage imbalanced datasets to optimize model performance. Deploy and host machine learning models, ensuring their scalability and reliability in production environments. Monitor and maintain models in production, implementing feedback loops for continuous improvement. Identify and mitigate biases in models to ensure fairness and accuracy. Collaborate with cross-functional teams to understand business needs and translate them into technical requirements. Document processes and model performance, providing insights and recommendations.