Senior Data Scientist, Cloud Gaming - Prescriptive Analytics and Optimization

This senior data scientist role focuses on prescriptive analytics and optimization for real-time cloud gaming, delivering scalable ML/AI and optimization solutions for routing, scheduling, and capacity management at NVIDIA.

Location

Santa Clara, CA (onsite)

Compensation

USD 184,000 - 287,500 per year

Experience and Education

Minimum 6 years of experience with a BS/MS or equivalent experience, or a PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.

Responsibilities

• Develop and deploy scalable ML, AI, and optimization models to improve demand forecasting, optimize capacity allocation, and implement user-specific feature engineering for real-time cloud gaming services.
• Create reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions toward targeted business outcomes.
• Apply domain knowledge of the product and software stack to identify data inconsistencies and enhance model performance, especially in the context of optimization results.
• Analyze complex datasets to identify trends and patterns using supervised and unsupervised learning to inform prescriptive solutions.
• Design and enhance real-time prescriptive scheduling pipelines using linear programming and constraint optimization to improve capacity utilization and user retention.
• Increase organizational productivity by mining petabytes of data for actionable insights, often delivered as prescriptive recommendations.
• Collaborate with a diverse set of partners to gather requirements, design robust solutions, and guide the team toward impactful results.
• Leverage agentic AI to deliver advanced automation and programming solutions for complex analytical problems.

Requirements

• 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 focus on prescriptive analytics and optimization.
• Strong foundation in probability, statistics, AI/ML, prescriptive modeling, and optimization methodologies such as linear programming, network flow, decision theory, and multi-armed bandit.
• Proficient coding skills, primarily Python, with the ability to write readable, testable, maintainable, and extensible code; experience with optimization libraries such as Google OR-Tools.
• Experience with data storage and processing tools and the ability to address issues in running large-scale software across substantial clusters.
• Solid experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality affects performance.

Technologies

• Python
• SQL
• Delta Lake
• Apache Spark
• Databricks
• MLflow
• Grafana
• Elasticsearch
• Google OR-Tools
• Kubeflow

Benefits

• Equity
• Benefits

What you will be doing

• Develop and deploy scalable ML, AI, and optimization models to improve demand forecasting, optimize capacity allocation, and craft user-specific features for real-time cloud gaming services.
• Build reusable data ingestion, processing, and analysis frameworks to support dynamic user interventions for targeted business outcomes.
• Apply product and software stack knowledge to resolve data inconsistencies and boost model performance within optimization contexts.
• Identify and interpret patterns in complex data using supervised and unsupervised methods to inform prescriptive solutions.
• Enhance real-time prescriptive scheduling pipelines through linear programming and constraint optimization to maximize capacity utilization and retention.
• Drive organizational productivity by mining vast data stores for actionable insights and prescriptive guidance.
• Collaborate with partners to define requirements, craft robust solutions, and lead the team toward meaningful results.
• Utilize agentic AI to deliver automation and programming solutions for challenging analytical problems.

What we need to see

• 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.
• Solid background in probability, statistics, AI/ML, prescriptive modeling, and optimization methods (eg, linear programming, network flow, decision theory, multi-armed bandit).
• Strong coding ability in Python with experience in optimization libraries such as Google OR-Tools; ability to write clean, maintainable code.
• Experience with data storage and processing tools and handling large-scale distributed software across clusters.
• Proficiency in data cleaning, aggregation, transformation, and extraction, with awareness of data quality impacts on performance.

Ways to stand out from the crowd

• Strong collaboration and presentation skills for working with multiple partners, with the ability to explain complex analytical solutions and their business implications.
• Experience in time series analysis and forecasting for demand prediction in optimization contexts is advantageous.
• Experience operating active ML production pipelines (MLflow, Kubeflow) with a focus on deploying and monitoring optimization models is advantageous.