(2025 Graduate) Data Scientist - Machine Learning and Analytics

Tencent Games was established in 2003. We are a leading global platform for game development, operations and publishing, and the largest online game community in China.

Tencent Games has developed and operated over 140 games. We provide cross-platform interactive entertainment experience for more than 800 million users in over 200 countries and regions around the world. Honor of Kings, PUBG MOBILE, and League of Legends, are some of our most popular titles around the world. Meanwhile, we actively promote the development of esports industry, work with global partners to build an open, collaborative and symbiotic industrial ecology, and create high-quality digital life experiences for players.

Level Infinite is Tencent’s global gaming brand. It is a global game publisher offering a comprehensive network of services for games, development teams, and studios around the world. We are dedicated to delivering engaging and original gaming experiences to a worldwide audience, whenever and wherever they choose to play while building a community that fosters inclusivity, connection, and accessibility. Level Infinite also provides a wide range of services and resources to our network of developers and partner studios around the world to help them unlock the true potential of their games.

Responsibilities:

• We are hiring a Data Scientist for the Machine Learning and Advanced Analytics DS team
• Apply machine learning and advanced analytic methods to solve challenging problems and deliver scalable game solutions in development, publishing, and live operations
• Establish scalable, efficient, automated processes and provide end-to-end data solutions with large-scale data analysis, experimentation, machine learning/deep learning/reinforcement learning model development, validation, and serving
• Interact cross-functionally with various teams and provide actionable business insights for stakeholders

Requirements:

• Masters or PhD program in a quantitative discipline such as statistics, machine learning, computer science, math, economics, etc
• Expertise in one or more of the following areas: machine learning & statistical learning, deep learning, reinforcement learning, statistical analysis, experimentation, NLP, computer vision, recommendation system, and any other data science-related domains
• Experience utilizing analytics, inference, experimentation, or machine learning techniques in real-world applications is preferred
• Excellent knowledge of data science methods and best practices, such as data analysis and visualization, supervised learning, unsupervised learning, and time series
• Proficient in SQL and Python