In 2009, Riot released its debut title League of Legends ("LoL") and over 100 million people now play the game every month. Whether you're in Rio, Seoul, or Moscow, you can find an excited and engaged community of League players.

Riot's Data Discipline builds tools to understand and delight our global audience of millions of 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, and that's where you come in. As we continue to deliver and scale content to passionate gamers, our discipline has challenges and opportunities centered on crafting, building, and maintaining data products that support the organization’s growth. Whether you are a Data Scientist modeling game systems, a Data Engineer building a parallelized data pipeline, or a Data Architect organizing data in ways that make data products more efficient and dependable, we need you to help to push forward our “Player Experience First” aspirations.

Riot Data Scientists combine their wide technical expertise across data processing, automation, machine learning ("ML"), artificial intelligence ("AI"), and experimental design to inform decisions and develop data-powered products. As a Senior Data Scientist, you’ll dive into projects that focus on cross-team objectives. You’ll provide other data scientists with a north star of “what extraordinary data science should look like". You are the lead for complex or significant technical work, where the problem requires evaluation of intangibles. You can customize methods to suit an unusual data problem and juggle technical dependencies. You work at a multi-team scale, influencing product vision, technical designs, and other scientists' development across an organization. You lead by example, but you also lead by leading - you deliver high impact work while elevating others' data science craft.

This specific role sits with the League Data Central team, which is the hub for all Data Science and Data Engineering on LoL. The team collaborates on multi-functional projects that range from in-game features to content design to infrastructure. In a world of high volume and complexity, you will develop products that bring personalization, optimization, and scale to players.

Responsibilities:

  • Design and implement data science systems (ML, AI, optimization, and statistics)
  • Improve the scale and efficiency of data science approaches
  • Pair with data engineers to design deployments and pipelines
  • Elevate team technical craft with peer reviews, paper reading, and tech prototyping
  • Identify new product opportunities and collaboratively develop them with partners
  • Represent data products to non-technical partners and collaborators

Desired Qualifications:

  • 5+ years data science industry experience
  • 3+ years "productionalizing" code into live systems
  • 2+ years hands on experience with petabyte-processing-capable technologies such as Spark or Hadoop
  • Experience setting up and interacting with cloud infrastructure (e.g., AWS)
  • Professional proficiency in Python and SQL
  • An MS or PhD in Engineering, Computer Science, Physics, Statistics, or related field

Applicable Technologies/Skills:

  • Understand trade-offs between data infrastructure and database systems
  • Familiarity with iterative development methodologies like Scrum, Agile, etc.
  • Familiarity with Java, Scala, C++
  • Familiarity with git

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance relating to an applicant's criminal history (LAMC 189.00).

 

 

#LI-JM1