Riot's Data developers build tools to understand and delight our worldwide players using petabytes of data and state-of-the-art data processing technology. Handling the potential these data offer is a tremendous and complex task. As we continue delivering and scaling content to passionate gamers, our discipline has challenges and opportunities centered on crafting, building, and maintaining data products that support our growth. Whether you are a Data Scientist modeling game systems, a Data Engineer bringing scale and efficiency to systems, or a Data Architect organizing data in ways that make data products more player-focused and dependable, we need you to help push forward our "Player Experience First" goals.As a Data Science Intern on the League Data Central team, you will build data products to support the games and functions of the organization. You will report to the Data Science Manager on League Data Central, the hub for all Data Science and Data Engineering for League of Legends, Teamfight Tactics, and Wild Rift. The team collaborates on cross-functional projects that range from in-game features to content design to infrastructure. In a world of high volume data, you will develop products that bring personalized experiences to players, optimize our strategy, and refine in-game features.
Responsibilities:
-Work closely with game feature teams to optimize the way that we design and serve to players
-Partner with game designers and engineers to design and implement data products
-Explore the application of data science techniques to games in development and production
Required Qualifications:
-Currently enrolled in an M.S. or Ph.D. program in statistics, engineering, computer science, artificial intelligence, or a related quantitative field (math, physics, etc.)
-Available to work full-time hours for 10-12 weeks at the indicated office during the summer
-Experience in statistics, statistical modeling, and optimization
-Experience processing data and build machine learning models using Python
-Experience with databases and SQL
Desired Qualifications:
-Basic understanding of data warehousing, relational databases (e.g., MySQL), and distributed data processing or storage systems (e.g., Spark, Flink, Hadoop)
-Basic experience withSpark, or other big data tech (e.g., Hadoop)
-Basic experience with cloud data tools (e.g., AWS, GCP)
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