Electronic Arts

The Finance organization at EA is transforming how insights, automation, and technology enable faster, smarter decisions across all Finance disciplines. As part of our multi-year Finance Transformation, we are modernizing analytics and AI capabilities that unify data, platforms, and processes to create a scalable, intelligent Finance ecosystem.

We are seeking an Analytics Manager to build analytics and machine learning solutions that reduce manual work, improve forecast and reporting efficiency, and enable automation across Controllership, Tax, Treasury, and Strategic Finance. You will design thin Direct Lake models, trusted measures, predictive models, and executive-ready visuals that provide real-time, actionable insights.

This role partners closely with Finance Technology, Data & Insights, and other Finance teams to develop reusable models, templates, and data assets that strengthen the analytical foundation for automation and AI-driven insights.  You will report to the Senior Manager, FinTech Data and Insights. This is a hybrid role defined as minimum of 3 days a week from an EA Office.  

Responsibilities & Outcomes

Finance Data & Modeling

• Build and maintain thin Direct Lake semantic models and report templates for GL performance, Opex and headcount, project finance, and revenue analysis.
• Develop predictive and machine learning models that identify financial trends, forecast key metrics, and improve planning accuracy.
• Design parameterized Dataflows and Warehouse views to support self-service analytics across all Finance teams.
• Implement RLS and OLS patterns, aggregation strategies, and Delta hygiene to ensure scalability and performance.
• Use notebooks for data preparation, feature engineering, and model writeback when required.

Transformation & Enablement

• Collaborate with Finance Technology and Data & Insights teams to align models with governed datasets, enterprise data standards, and automation strategy.
• Partner with Finance stakeholders to identify opportunities for process automation and predictive analytics.
• Document models, maintain metadata, and lead enablement sessions to strengthen self-service analytics capabilities.
• Promote adoption of standardized models, templates, and visualization frameworks to improve consistency and reduce reporting cycle time.

AI & Automation Integration

• Build and deploy machine learning and predictive models that enhance Finance's ability to forecast, simulate, and optimize business outcomes.
• Integrate AI and automation capabilities into Finance workflows, driving measurable efficiency and insight generation.
• Contribute to Finance's readiness for generative and advanced analytics applications through reusable, high-quality datasets.

Required Qualifications

• 5 plus years of experience in analytics, business intelligence, or data science with deep Power BI and SQL expertise.
• Hands-on experience with Microsoft Fabric Lakehouse or Warehouse, Direct Lake, and DAX at enterprise scale.
• Experience building and deploying machine learning or predictive models using Python, PySpark, or related frameworks.
• Strong understanding of Finance concepts including plan vs. actuals, variance analysis, and scenario modeling.
• Experience supporting Finance transformation, AI, or analytics modernization initiatives.