Phillip Koskinas
About Phillip Koskinas
Phillip Koskinas is a Senior Manager and Anti-Cheat Lead at Riot Games, where he has worked since 2014. He specializes in scripting languages and data pipelines to develop effective anti-cheat measures using tools like Hadoop, Python, and Spark.
Work at Riot Games
Phillip Koskinas has been employed at Riot Games since 2014, serving as the Senior Manager and Anti-Cheat Lead. In this role, he focuses on developing and implementing effective anti-cheat measures to enhance game security. His work involves utilizing advanced technologies and methodologies to combat cheating behaviors in online gaming environments. Based in Los Angeles, California, he has contributed significantly to the company's efforts in maintaining fair play across its gaming platforms.
Education and Expertise
Phillip Koskinas holds a Bachelor of Business Administration (BBA) in Actuarial Science from Georgia State University. His educational background provides a strong foundation in mathematical principles, which he applies in his current role. He has developed expertise in scripting languages and data pipelines, which are essential for creating robust anti-cheat systems. His knowledge in statistical analysis and data visualization further supports his efforts in identifying and mitigating cheating behaviors.
Background
Before joining Riot Games, Phillip Koskinas gained diverse work experience in various roles. He worked as a Mathematics Tutor at Georgia State University from 2011 to 2013, where he assisted students in understanding mathematical concepts. He also held positions as a Delivery Driver at Domino's and as a Sandwich Artisan at Subway. These roles contributed to his development of strong communication and problem-solving skills, which are beneficial in his current position.
Technical Skills and Tools
Phillip Koskinas specializes in utilizing a combination of Hadoop, Python, and Spark to enhance game security systems. His technical skills include high-powered queries and data wrangling, which are crucial for supporting anti-cheat operations. He employs statistical analysis techniques to develop predictive models for cheat detection, leveraging his strong background in mathematical probability to inform his strategies.