Electronic Arts

Advanced Data Analyst - FC Live Service Forecasting

Our FC Data & Analytics team is looking for an Advanced Analyst to support our Live Service Analytics group. Reporting to the Analytics Manager, you will be part of a growing team focused on providing data and insights around player behaviour and live content performance within the FC franchise. We're looking for someone with a passion for using historical data to project future performance, and an expertise in combining the science of predictive modelling with the art of incorporating business & financial factors into their projections. 

What you'll do on our team: 
● Own part of our FC Live Service Forecast that forms the foundation of how we measure the performance of our product. 
● Employ an extensive toolkit of financial modelling techniques, time series analysis, and a deep knowledge of their use cases to determine the best possible solution to a wide range of business problems. 
● Develop a rigorous and robust model that projects our live service’s funnel metrics to a high degree of fidelity, taking into account player behaviour, in-game content, and macroeconomic trends. 
● Collaborate with partners across Product Management, Finance, and Commercial teams to align on projections, and keep the business updated on how our latest live service performance impacts our model’s assumptions. 
● Run risk and opportunity scenarios based on live content plans, new feature additions, and other potential changes in the FC product. 
● Lead presentations to diverse audiences including senior and executive level management. 

What we're looking for:
● A degree in a quantitative discipline (Analytics, Statistics, Mathematics, Econometrics, Finance, or similar). 
● 7+ years of experience in a data-driven role performing quantitative analysis with big data to help guide decisions 
● 4+ years of experience developing financial/product performance projections and forecasts using varying modelling techniques. 
● Experience in statistical and/or time series modeling for predictive purposes 
● Expertise in SQL and ability to extract data from large data sources with differing structures 
● Proficient in analyzing large datasets using programmatic tools (e.g. Python, R) 
● Deep experience with data visualization software (e.g. Tableau, PowerBI, Looker) 
● Comfortable presenting analysis results in an executive facing environment