Nvidia Senior Data Scientist - Cloud Gaming 

United States, Texas 

871037671

What you'll be doing:

• Build and deploy scalable ML/AI models to optimize the demand forecasting, capacity allocation and user specific feature-engineering for the real time cloud gaming service.

• Build improvements to real-time prescriptive scheduling pipelines to maximize capacity utilization and user retention.

• Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance.

• Develop re-useable framework deployments for data ingestion, processing and analysis.

• Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques.

• Improve productivity of the org by wrangling petabytes of data to provide actionable insights to business and engineering.

• Work with a variety of stakeholders to understand requirements, design solutions, and guide the team to deliver results.

• Leverage agentic AI to deliver best-in-class programming solutions.

What we need to see:

• BS/MS or equivalent experience with 5+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, or related quantitative fields.

• Strong background knowledge and practical experience in probability, statistics, and AI/ML.

• An outstanding track record of past projects related to the research and application of data science.

• Strong coding skills, including the ability to write readable, testable, maintainable, and extensible code (primarily Python)

• Experience with common tools for data storage and processing, including drilling into problems of running large-scale software in a big network.

• Strong experience in data cleaning, aggregation, transformation, and extraction.

• Good interpersonal and presentation skills in working with multiple partners.

• Experience with time series analysis is a plus.

• Experience in active ML production pipelines is a plus (MLflow, KubeFlow).