Electronic Arts

We are hiring a Lead Data Scientist – Battlefield to join our Data & Insights (D&I) Data Science team, reporting to a Senior Manager of Data Science. The Data Science team partners with EA studios to build scalable AI/ML solutions that enhance player experience, game design, and live service performance.

You will bring expertise in the area of AI, ML, and engineering. You will also lead efforts related to life cycle management, progression, in-game economies, and player experience, specifically, within the Battlefield franchise.

Responsibilities

• Work directly with Battlefield game team/partners (internal clients) to understand their offerings/domain and create data science products and solutions to solve for their use cases.

• Apply problem-driven, AI/ML approaches to improve player experience, engagement, retention, and monetization systems.

• Develop plans to generalize products across the franchise with our engineering partners.

• Establish rigorous experimental design standards (A/B testing, causal inference, system experimentation) to produce actionable insights.

• Collaborate with engineering partners to productionize models within live environments and gameplay systems.

• Design and enhance data pipelines that process petabyte-scale telemetry data using technologies such as AWS, S3, Kubernetes, GCP, Python, Apache Kafka, and Hive.

• Develop algorithms and statistical models for forecasting, player state prediction, churn analysis, progression balancing, and economic system tuning.

• Communicate complex analytical concepts to technical and non-technical partners, influencing strategic decisions.

• Mentor other data scientists and contribute to shared best practices across the D&I organization.

Required Qualifications

• Graduate degree in Statistics, Mathematics, Computer Science or another quantitative field encouraged.

• 6+ years of professional experience manipulating data sets, building statistical models and productizing models along with experience applying Data Science methodologies to real-world problems.

• Expertise in the gaming space, understanding typical business models, game development practices and technology.

• Experience building applied models, systems or projects in the following areas: retention, economics/systems experiments, ad segmentation, ML/AI engineering and deployment technology.

• Experienced in analyzing extremely complex, multi-dimensional data sets with a variety of tools.

• Familiarity with at least one scripting language: Python or R.

• History of mentoring junior team members.

• Knowledgeable about data warehouse and non-relational data techniques to work with engineering partners.

• Experience using query languages and other analytic tools.