About the job

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 video games, including Madden NFL football, FIFA Soccer , NHL® hockey, NBA LIVE basketball, and EA SPORTS UFC .

Millions of EA SPORTS players generate billions of events every day. We use high-volume data streams to quickly detect and address game security threats. The Game Security Data Scientist uses big data, machine learning, and visualization techniques to explore and implement improvements to the security of the EA SPORTS player experience.

You will be at the crossroad of several hot areas: Data Science and Engineering, Security, and Software Development. You don't need to have experience in all the four areas but we are looking for someone who can demonstrate a solid background and grow in other areas. You adopt a security mindset to predict the adversaries' moves. You can use multiple statistical and machine learning methods to detect anomalies and fraudulent behavior.

Responsibilities

• Collaborate with team members across multiple disciplines to understand the data behind game features, user behaviors, the security landscape, and business goals.
• Analyze data from several large sources, then automate solutions using scheduled processes, models, and alerts.
• Work with partners to design and improve metrics that guide our decisions by summarizing the state of game security.
• Detect patterns associated with fraudulent accounts and anomalous behavior.
• Solve scientific problems and create new methods independently.
• Translate requirements and security questions into data insights.
• Set up monitoring and alerting mechanisms so our leadership is always aware of the security posture.

Qualifications

• Post Graduate degree in Computer Science, Mathematics, or Electrical Engineering with specialization in machine learning, information security, artificial intelligence, decision support/making or other related fields.
• Experience with SQL and no-SQL databases.
• 2+ years of applied machine learning and analytics experience and familiarity with standard techniques, relevant tools and libraries.
• Familiarity with programming languages such as Python, R, Java, or C/C++.
• Use Bayesian models and Social network analysis (SNA) tools to develop entity behavior analytics that demonstrate a holistic view of the bad activities.