Data Science Intern, Cloud Gaming

About NVIDIA

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.

The Cloud Gaming Data Science team of GeForceNow at Nvidia is building innovative efficiency solutions that encompass collection, processing, visualization, analysis, root cause detection, model based prediction for both qualitative and quantitative data from millions of our end users. Our data sources include traditional personal computers, mobile devices, TVs, servers and distributed Web services. Active projects include analysis for cloud gaming experience, user behavior and churn profiling, user base segmentation, actionable cluster identification, smart personalized recommendations and chatbots, lifetime value analysis, capacity management and suspicious activity detection. We are seeking an intern to add intelligence and analysis capabilities to various user-facing and backend projects, helping to deliver the power of data to users across the world!

What You'll Be Doing as a Data Science Intern, Cloud Gaming

• Develop AI/ML models at scale to address requirements of Efficiency, Retention and Security.
• Develop and deploy prescriptive analytics solutions for efficient cloud capacity allocation.
• Identify, analyze, and interpret trends or patterns in sophisticated data sets using supervised and unsupervised learning techniques including user behavior like retention and churn.
• Build scalable algorithms for toolchains based on data processing and machine learning to root cause production issues.
• Improve efficiency of the organization by wrangling petabytes of data using groundbreaking machine learning tools to provide actionable business and engineering insights.

What We Need To See

• Pursuing MS or PhD in Data Science, Computer Science, Operations Research, Statistics or related quantitative fields.
• Validated background knowledge in Statistical Analysis.
• Experienced in building Machine Learning and Deep Learning models using techniques like clustering, classification, outlier analysis, hyperparameter tuning, feature engineering.
• Strong coding skills, including the ability to write readable, testable, maintainable and extensible code (primarily Python/SQL including libraries like Pandas).
• Good interpersonal, presentation and reporting skills are important.

Ways To Stand Out From The Crowd

• Experience in active ML production pipelines (MlFlow, KubeFlow).
• Background with common tools for data storage and processing (e.g. Spark, Hadoop Map/Reduce, Hive, Cassandra).
• Experience building prescriptive models using methods like constraint optimization (CP-SAT, Gurobi).
• Experience working on an Agile or iterative development team.

Key skills/competency

• Data Science
• Machine Learning
• AI/ML Models
• Cloud Gaming
• Statistical Analysis
• Python
• SQL
• Data Processing
• Prescriptive Analytics
• User Behavior Analysis
• Deep Learning