Location: Singapore/ Amsterdam/ Palo Alto

Tencent Games Global Publishing Center Tech Team is the international unit of Tencent Games, a leading global platform for game development, publishing and operation. Aiming to improve our games and transform the gaming industry, our mission is to solve the toughest challenges in gaming with technology.

With offices in Singapore and around the world, our growth strategy is to build upon attracting the best talent and creating an amazing work atmosphere that balances the energy of a start-up with the resources of a global innovation leader. As the world’s leading technology company, we maintain an entrepreneurial spirit and an open mindset.

If you are passionate about the gaming industry and eager to do groundbreaking work in a friendly, cross-cultural environment, we can provide unparalleled stability, resources, access to more than a billion players, and an international perspective.

If you like us are ambitious and self-driven, we invite you to explore Tencent Games Global Publishing Center Tech Team and take challenges that will create new adventures for billions of players.

Come join us and explore the power of data driven gaming.

Responsibilities

Build machine learning models and utilize data analysis to deliver scalable solutions to business problems.
Run A/B experiments, gather data, and perform statistical analysis.
Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in game production, publishing and live-ops.
Research new machine learning approaches.

Qualifications and Skills

M.S., or Ph.D. in a quantitative discipline like computer science, machine learning, and math/statistics; Ph.D. with Strong publication record preferred;
3+ years of experience of building machine learning models for business application preferred;
Breadth and depth knowledge of machine learning algorithms and best practices;
Expert in statistical analysis (probabilities, hypothesis testing, multivariate analysis, time series analysis, generalized linear model, A/B experiments) ;
Experience programming in Python, SQL, Java, C++ or related language;
Experience with Big Data technologies such as Hadoop, Spark, Pig, Hive, etc. preferred.