Data Science Intern

This Data Science Intern role at Electronic Arts is a hybrid internship in Hyderabad for computer science and software engineering students. You will join the EA Digital Platform team and work on machine learning models for live games. Daily work covers data cleaning, model building, deployment and monitoring.

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Why This EA Data Science Internship Stands Out

* The work is built around real machine learning problems for games that have tens of millions of monthly active users, so you are not just playing with toy datasets. * You get exposure to the full model cycle, from cleaning data to deploying, monitoring and improving models in production. * It is not a beginner-level internship. The skills list is long, so it fits you best if you already have a few ML projects behind you.

* Work with product managers, senior engineers and teammates to understand what is needed, then prototype and build large-scale applications. * Build and implement custom machine learning models for real game and platform problems. * Clean, preprocess and analyse large datasets while keeping the data accurate and reliable. * Handle imbalanced datasets so the models perform properly, and check models for bias to keep them fair. * Deploy and host models, then monitor them in production and set up feedback loops to keep improving them. * Document your process and model performance, and share insights and recommendations with cross-functional teams.

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Technical Skills

* Python or R, with experience in libraries such as TensorFlow, PyTorch or Scikit-learn. * Solid Computer Science basics: algorithms, data structures, design patterns and CI/CD processes. * Data preprocessing techniques and handling imbalanced datasets. * Model evaluation metrics and methods to spot and reduce bias. * Familiarity with deploying models on cloud platforms (AWS, GCP or Azure).

* Good understanding of LLM architecture, fine-tuning and training LLMs. * Solid understanding of AI agents. * Ability to take high-level direction, work through unclear problems and turn business requirements into technical design.