Note: The job is a remote job and is open to candidates in USA. NVIDIA is building an innovative data platform for advanced analytics and real-time cloud gaming routing and scheduling. The Senior Data Scientist will develop and deploy machine learning, prescriptive analytics, and optimization models; improve data and scheduling pipelines; analyze complex datasets; and collaborate with partners to deliver scalable cloud gaming solutions.
Responsibilities
- Build and deploy scalable ML/AI and optimization models to enhance demand forecasting, optimize capacity allocation, and develop user-specific feature engineering for real-time cloud gaming services
- Develop reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions for targeted business outcomes
- Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance, especially in the context of optimization outcomes
- Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques, informing prescriptive solutions
- Design and implement improvements to real-time prescriptive scheduling pipelines, using techniques like linear programming and constraint optimization, to enhance capacity utilization and user retention
- Improve productivity of the organization by mining petabytes of data for actionable insights for business and engineering, often through prescriptive recommendations
- Collaborate with a variety of partners to understand requirements, design robust solutions, and guide the team to deliver impactful results
- Leverage agentic AI to deliver best-in-class automation and programming solutions for complex analytical problems
Skills
- BS/MS (or equivalent experience) with 6+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative fields, with a strong emphasis on prescriptive analytics and optimization
- Strong background knowledge and practical experience in probability, statistics, AI/ML, prescriptive modeling, and optimization methodologies (e.g., linear programming, network flow, decision theory, and multi-armed bandit)
- Strong coding skills, including the ability to write readable, testable, maintainable, and extensible code (primarily Python), with experience in libraries or tools relevant to optimization (e.g., Google OR-Tools)
- Experience with common tools for data storage and processing, including drilling into problems of running large-scale software across large clusters
- Strong experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality impacts performance
- Good interpersonal and presentation skills in working with multiple partners, adept at explaining intricate analytical solutions and their business implications
- Experience in time series analysis and forecasting for demand prediction in optimization contexts is a plus
- Experience in active ML production pipelines (MLflow, Kubeflow) with a focus on deploying and monitoring optimization models is a plus
Benefits
- Equity
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