Data Science Intern - Experimentation

Key Skills

Python Programming, SQL, R Programming, Supervised learning, Unsupervised learning

Job Description

Tencent Games Global Publishing Technology 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 Palo Alto 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.

Responsibilities

• We are hiring internships for the experimentation team. 
• Collaborate with cross-functional teams to run end-to-end experiments, including experiment design, experiment analysis, as well as communicating experiment results to partner and leadership team for making business decisions.
• Conduct applied research and develop methodology in experimentation, causal inference, causal learning, and statistical models to solve business problems and create user value. 
• Interact cross-functionally with various teams and provide actionable business insights for stakeholders. 

Qualifications and Skills

• Currently enrolled in 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: statistical analysis and inference, experimentation, causal inference, causal learning, and time series;
• Experience in utilizing analytics, inference, experimentation, or machine learning techniques in real-world applications preferred; 
• Good knowledge in general data science methods and best practices, such as data analysis and visualization, experimentation, causal inference, supervised learning, unsupervised learning, time series, probabilities, and sampling methods; 
• Proficient in SQL and Python, R, or other related programming languages.