Data Science Intern - Machine Learning and Analytics

Key Skills

Python Programming, SQL, Machine learning techniques, Deep Learning, Natural Language Processing (NLP), R Programming, OpenCV, Computer Vision (CV), 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 applied machine learning and growth DS team. 
• Join a highly-skilled data science team?to mine through big data by applying advanced analytic methods, to solve challenging problems and to deliver scalable solutions in game development, publishing, and live-ops.
• Establish scalable, efficient, automated processes and provide end-to-end data products with large-scale data analysis, experimentation, machine learning/deep learning/reinforce learning model development, validation, and serving. 
• Interact cross-functionally with various teams and provide actionable business insights for stakeholders. 
• Research new approaches in the field of machine learning, experimentation, causal inference, etc.

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: machine learning & statistical learning, deep learning, reinforcement learning, statistical analysis, experimentation, NLP, computer vision, recommendation system, and any other data science related domains;
• Experience in utilizing analytics, inference, experimentation, or machine learning techniques in real-world applications preferred; 
• Good knowledge in data science methods and best practices, such as data analysis and visualization, supervised learning, unsupervised learning, and time series; 
• Proficient in SQL and Python, R, or other related programming languages.