Senior Data Scientist - Machine Learning and Analytics

1 Month ago • All levels

About the job

Responsibilities:

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.

Tencent Games Advanced Data Group is part of the international unit of Tencent Games, a leading global platform for game development, publishing, and operation. Our mission is to solve the toughest challenges in gaming with advanced technology, aiming to improve our games and transform the gaming industry.
With offices in Palo Alto and across the globe, our growth strategy is centered on attracting top talent and cultivating an exceptional work environment. We aim to strike a balance between the dynamism of a start-up and the resources of a global innovation leader. As the world’s leading technology company, we foster an entrepreneurial spirit and an open mindset.
If you are passionate about the gaming industry and eager to make a significant impact in a friendly, cross-cultural environment, we can offer unparalleled stability, resources, access to more than a billion players, and an international perspective. At Tencent Games, we are committed to pushing the boundaries of innovation in the gaming industry.

Responsibilities

● We are hiring a senior 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:

Qualifications and Skills

● Graduated with a master’s or Ph.D. 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.

#LI-RL1

About The Company

Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life of people around the world.


Founded in 1998 with its headquarters in Shenzhen, China, Tencent's guiding principle is to use technology for good. Our communication and social services connect more than one billion people around the world, helping them to keep in touch with friends and family, access transportation, pay for daily necessities, and even be entertained.


Tencent also publishes some of the world's most popular video games and other high-quality digital content, enriching interactive entertainment experiences for people around the globe.


Tencent also offers a range of services such as cloud computing, advertising, FinTech, and other enterprise services to support our clients' digital transformation and business growth.


Tencent has been listed on the Stock Exchange of Hong Kong since 2004.

Guangdong Province, China (On-Site)

Auckland, New Zealand (On-Site)

Shanghai, China (On-Site)

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