Data Analyst - EA SPORTS FC

Our FC Data & Analytics team is looking for a Data Analyst to support our Live Analytics group. Reporting to an Advanced Analyst, you'll be part of a growing group working with the franchise's product & content teams.

We're looking for someone with experience analyzing and isolating the impact that product actions can have on our live service’s business performance. In this role, you'll be a data explorer and investigator, identifying major trends in our data and diving into them to diagnose why those trends are happening. Examples of projects you may work on include: assessing campaign content impact, developing reports that track key metrics across various user cohorts, and analyzing the effects that our live content has on overall player engagement.

What you'll do on our team:

• Receive questions from our partners, determine the best ways that our data can help answer them, and provide those insights and recommendations through dashboards, reports, or presentations.
• Develop pointed insights to help our partners make informed decisions about in-game campaign planning.
• Create dashboards and reports that enable our team and our partners to identify trends in our data.
• Explore user behaviour patterns to identify opportunities to improve the player experience.
• Investigate how live content and campaigns impact our in-game player economy.
• Present analyses and findings to our partners in a clear and understandable way employing strong data visualization and storytelling skills.

What we're looking for:

• A bachelor's degree in Business, Statistics, Mathematics, Economics, Data Science, Analytics, or a related field.
• 3+ years of experience in an analytics role performing quantitative analysis with big data to help guide decisions.
• Proficiency in SQL and ability to extract data from large data sources with differing structures.
• Proficiency with at least one data visualization software (e.g. Tableau, PowerBI, Looker).
• Strength in presenting complex data insights in a clear and concise manner to a wide audience.
• Experience analyzing large datasets in programmatic analysis tools (e.g. Python, R).