Electronic Arts

Frostbite is EA’s proprietary game engine that comes equipped with tons of tools and technologies designed to build incredible games. Our in-house engine offers the unique ability to adapt to each game while working hand-in-hand to prioritize what to build. Our goal is to empower creators all over the world to bring their best ideas to life by creating an engine that amplifies innovation across every discipline. Learn More: ea.com/frostbite

At Frostbite, we believe that data drives quality, accountability, and innovation in game engine development. We are growing our Frostbite Analytics team in service of this mission, and we want you to join us!

As a Data Scientist on the Frostbite Analytics team, you will report to the Senior Analytics Manager and work side-by-side with the Continuous Development team. Your projects will focus on enhancing developer workflows, increasing build farm efficiency, and improving automated failure triage, allowing engineers to work faster and with greater confidence in their code submissions.

We offer a hybrid working model with three days per week in office. 

Responsibilities

• Design, implement, and maintain data-driven solutions to improve build-farm operations, CI/CD workflows, and automated test failure analysis.
• Analyze telemetry, test results, and other data to identify patterns, inefficiencies, and optimization opportunities.
• Integrate actionable analytics into developer tools through dashboards, REST APIs, and automated processes.
• Work with data engineers to improve data processing and storage for efficiency, latency, and cost-effectiveness.
• Communicate insights and recommendations to leadership and internal partners in business-friendly language

Requirements 

• 2+ years of experience in data science or ML ops, or related analytics roles
• Master's in Computer Science, Statistics, or equivalent experience in a related field

Technical Skills

• Proficiency in SQL and Python (Scala, C++, or C# is a plus), with experience in real-time analytics and data transformation workflows.
• Familiarity with a range of quantitative methods for detecting failures, predicting outcomes, and optimizing processes, such as anomaly/time-series analysis, classification models, and reinforcement learning.
• Experience working with telemetry data in software development or similar context
• Experience with version control systems like Perforce or Gitlab. 
• Experience with ML and analytics platforms such as Databricks or SageMaker for developing and deploying models at scale.
• Knowledge of CI/CD systems, automated build environments, and developer-facing analytics tools is a plus.

Soft Skills

• Curious and analytical: You uncover patterns in data, ask the right questions, and explore new methods to foster continuous improvements that connect to the bigger picture.
• Collaborative: You proactively seek out feedback and diverse perspectives, ensuring solutions are well-designed, scalable, and sustainable. You actively listen, adapt, and refine your approach for long-term impact.
• Impact-focused: You prioritize high-value solutions that lead to measurable improvements, balancing technical rigor with real-world constraints to enhance efficiency and automation.