Riot Games was established in 2006 by entrepreneurial gamers who believe that player-focused game development can result in great games. In 2009, Riot released its debut title League of Legends to critical and player acclaim. As the most played PC game in the world, over 100 million play every month. Players form the foundation of our community and it’s for them that we continue to evolve and improve the League of Legends experience.
We’re looking for humble but ambitious, razor-sharp professionals who can teach us a thing or two. We promise to return the favor. Like us, you take play seriously; you’re passionate about games. We embrace those who see things differently, aren’t afraid to experiment, and who have a healthy disregard for constraints.
That’s where you come in.
As Data Scientist, you'll develop advanced machine learning algorithms and statistical models to solve critical problems and help deliver awesome player experiences. You'll partner with product teams to implement data science models into live production systems. You'll bring fresh perspective to inform decision-making toward better player experience by translating player voice into insights using your top-notch modeling and analytic skills. You'll work closely with software engineers and combine your modeling and coding skills to create tools and infrastructure to empower and level-up data science at Riot.
- Educated: you've earned a BS or equivalent in Statistics, Computer Science, Math, Physics, or an applied quantitative field and likely added an MS or PhD in the same field to keep your BS company; you're more ninja than rockstar, preferring precision strikes to chest-thumping grandstanding; you have broad knowledge of machine learning, statistics, algorithm design, or software engineering
- Experienced: you've earned badges in statistical modeling, machine learning, distributed system, and database; you understand how to architect, implement, deploy, and maintain data science intensive applications in a cloud environment; you've also aced one or more of: deep learning, natural language processing, server architecture, software engineering, full stack web development, visualization – maybe earning a byline or two
- Big data passionate: you have a firm grasp of SQL and NoSQL databases, cloud environment, streaming, as well as the Hadoop ecosystem (Hadoop, Hive, Spark); you are very curious about the frontier of big data technology and committed to exploring the newest
- Up to code: you write well-abstracted and reusable code in Python, R, Java, or Scala; you freely navigate in Linux environment; you can stand up web applications; documentation, version control, and code review are in your blood
- Innovative and analytical: you're a skilled lateral thinker, pulling insight from data and free-associating yourself into unique perspectives on problems that stump lesser innovators
- A problem assassin: you conduct problem reconnaissance and termination with the skill and ruthlessness of Bond, but in an elegant, scalable manner; you easily identify and troubleshoot problems, quickly resolving issues
- Player-focused: as a gamer yourself, you know the importance of listening to player needs, especially the implicit needs that can only be uncovered by analyzing and understanding player data
- Analyze petabytes of player data, developing and testing data-fueled hypotheses, extracting useful information and turning it into helpful insight that can help us improve players' experiences
- Bring data science to life by working with software engineers to architect, develop, and deploy production level applications powered by advanced machine learning algorithms that can help us improve player experiences
- Bring data science to people through designing, prototyping, and implementing new ways to effectively communicate data science findings so that non-tech audiences can enjoy the beauty of advanced machine learning
- Develop tools that will help data scientists and stakeholders more efficiently plumb the dark depths of our very deep, very rich data stores
- Bring fresh perspective and new dimensions of analysis to bear on the challenge of identifying what we could do better; develop algorithms and predictive models to solve critical Riot Games problems and validate models to ensure proper behavior
- Work closely with fellow data scientists and engineers to identify opportunities and improve our data ecosystem
Don’t forget to include a resume and cover letter. We receive a lot of applications, but we’ll notice a fun, well-written intro that shows us you take play seriously.