Data Scientist - EA Sports Security
16 days ago
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 sport through industry-leading sports video games, including EA SPORTS Madden NFL , FC , NHL , NBA LIVE , and UFC .
EA SPORTS SECURITY – Data Scientist
The Sports Security team ensures that all EA Sports products are developed with the security and gameplay integrity of our players as a top priority. We partner with both platform development teams and game studios to ensure that security and game integrity issues are identified and resolved throughout the application and service lifecycle.
You will be a member of the Sports Security Data team reporting to the Lead Data Scientist. You will work with the team in developing excellent models to keep our games fair, fun, and free of cheaters.
As a Data Scientist on our Sports Security Data team, you will be a part of a global security team and will work with game and central tech development teams to:
- Work with team members across multiple disciplines to understand the data behind game features, user behaviors, the security landscape, and our 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 alerting mechanisms so our leadership is always aware of the security posture.
- Post Graduate degree preferably with specialization in machine learning, information security, artificial intelligence, decision support/making or other related fields.
- Experience with SQL and no-SQL databases.
- 4+ years of applied machine learning and analytics experience and familiarity with standard techniques, relevant tools and libraries. Academic experience can be included within those 4 years depending on its content.
- Familiarity with programming languages such as Python, R, Java, or C/C++.
- Familiarity with stats, modeling and data visualization.
- Experience with online gaming and interest in the cheating problem space
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- Familiarity with Big Data tools such as Hadoop, Spark, or Splunk.
- Experience with cloud platforms such as AWS, GCD or Azure.
- Exposure to Security in areas such as network/software security and an understanding of security data, attack vectors, and more.
- Experience with Visualization tools and libraries such as Tableau, Looker, or Matplotlib.
- Software development or Data engineering experience.
- Experience reviewing technical documents to advise on telemetry requirements.