Lead Data Scientist: Optimization for Cloud Gaming

NVIDIA; United States; On-site; USD 184,000 - 288,000; Full time

Job summary

NVIDIA is building an innovative Data Platform for real-time routing and scheduling at scale, using prescriptive modeling and optimization to improve cloud gaming performance worldwide. The role focuses on data collection, processing, visualization, anomaly detection, and predictive modeling across GPU availability, latency, and game performance.

You will develop scalable ML/optimization models, reusable data pipelines, and end-to-end solutions, collaborate with partners, apply time-series

Qualifications

• 6+ years of experience in data science, OR, or related fields with a focus on prescriptive analytics.
• Strong background in probability, statistics, AI/ML, and optimization methods.
• Proficient in Python with experience in optimization libraries.
• Experience with large-scale data processing on clusters.
• Excellent problem solving and collaboration skills.

Responsibilities

• Build and deploy scalable ML/AI and optimization models.
• Develop reusable data ingestion, processing, and analysis frameworks.
• Identify data quality issues and improve model performance.
• Analyze trends using supervised and unsupervised methods.
• Design improvements to real-time prescriptive scheduling pipelines.
• Mine large data for actionable business insights.
• Collaborate with partners to deliver impactful results.
• Leverage agentic AI for automation and programming solutions.

Skills

Prescriptive analytics

Optimization

Probability & stats

Python programming

ML basics

Data analysis

Education

BS/MS/PhD in quantitative field

Tools

Google OR-Tools

Apache Spark

Databricks

MLflow

Kubeflow

Job description

NVIDIA is building an innovative Data Platform for real-time routing and scheduling at scale, using prescriptive modeling and optimization to improve cloud gaming performance worldwide. The role focuses on data collection, processing, visualization, anomaly detection, and predictive modeling across GPU availability, latency, and game performance.

You will develop scalable ML/optimization models, reusable data pipelines, and end-to-end solutions, collaborate with partners, apply time-series