Posted on Nov 14, 2018 by EA Sports
EA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs and cross-platform digital experiences. EA SPORTS creates connected experiences that ignite the emotion of sports through industry-leading sports videogames, including Madden NFL football, FIFA Soccer, NHL® hockey, NBA LIVE basketball, NCAA® Football, Tiger Woods PGA TOUR® golf, SSX, and EA SPORTS UFC. For more information about EA SPORTS, including news, video, blogs, forums and game apps, please visit .
The Challenge Ahead:
As a Data Analyst you will play a key role in analyzing data to improve the player experience for our Sports titles. You should be a sharp, curious, and analytic individual who has a passion for diving into data and building models to understand how players are interacting with our games. Your insights will influence game design to drive improved acquisition, retention, and monetization.
What a Data Analyst does at EA:
- Ability to look at data and form hypothesis and test methodologies to identify bad actors.
- Evaluate business questions and determine the data needed to answer them.
- Produces strategic insights to help business stakeholders make business decisions.
- Presents analysis conclusions to business stakeholders in a clear, understandable, and valuable way.
- Identifies and clearly articulates insights drawn from data to include both in person and web- based presentation of findings and recommendations.
- Queries data necessary to conduct analyses.
- Advises product teams about data capture needs.
- Partners with Business Intelligence and Database Engineers to identify and manage data requirements to support high-quality analysis and reporting.
- Documents analysis methodologies, conclusions, and business actions taken.
- Considers analysis transparency and reproducibility as best practices.
- Communicates clearly (and as often as needed) with team members and business stakeholders.
- Supports senior team members with data identification and retrieval.
- BA or BS in Economics, Mathematics, Statistics, or related field
- SQL skills; experience querying large, complex data sets on a platform such as Redshift is a plus; experience on a big data (or NoSQL) platform such as Hadoop or Splunk is a plus
- Experience in data mining, machine learning, or statistical modeling
- Experience with a data visualization application; Tableau is a plus
- Experience with a statistical software package; R is a plus
- Experience with a scripting language; Python is a plus
- Ability to effectively communicate with people at various levels of business and technical expertise, including the ability to simplify difficult technical concepts