Principal Data Scientist - Cloud Gaming and AI

Details

Join the NVIDIA GeForce NOW cloud team, which enables users to play high-quality PC games on various devices without a dedicated gaming PC or console. GeForce NOW is built on NVIDIA GPU technology, including proprietary GPU architectures and software optimizations that provide high-resolution, high-frame-rate experiences with industry-leading low latency.

The team is building diagnostic, prescriptive, and AI-augmented analytics solutions covering data processing, visualization, anomaly detection, root-cause analysis, and predictive modeling for millions of end users. Current projects include real-time demand forecasting, constraint-optimized capacity allocation, dynamic per-session prescriptions, customer onboarding and Voice of Customer analytics, targeted customer outreach based on retention modeling, personalized diagnostic recommendations, and an LLM chatbot.

The technology stack includes Python, R, Pandas, JupyterLab, Spark, SQL, Databricks, MLflow, Delta Lake, Grafana, Kibana, Kubeflow, Elyra, Kubernetes, GitLab, CI/CD, MLOps, Kafka, and Amazon SQS.

Responsibilities

• Provide technical leadership to Data Scientists and Engineers working on the global deployment of GPU compute services at scale.
• Work with leadership and stakeholders to understand high-level requirements, develop a technical roadmap, design solutions, and guide the team in delivering results.
• Acquire and apply domain knowledge of the product and platform to lead the design, implementation, and deployment of AI/ML solutions that generate actionable insights and real-time prescriptive analytics for production services.
• Build and deploy real-time, scalable solutions for user diagnostics, LLM chatbots, dynamic suspicious activity detection, user-feedback-based clustering and alerting, and LLM-based actionable insight generation for engineering and management.
• Improve organizational productivity by processing petabytes of data with statistical, AI, ML, and LLM models to provide actionable, real-time insights.
• Use forecasting models and constraint-optimization solvers to improve capacity management, server efficiency, and end-user latency.
• Develop ML/AI predictive models with explainability for user retention and churn, and design outreach campaigns.
• Build multi-agent, self-learning harnesses to improve engineering productivity for analytics and deployments.

Requirements

• Master's degree, PhD, or equivalent experience in Data Science, Statistics, Mathematics, Physics, Operations Research, or a related quantitative field.
• 15+ years of software experience delivering large-scale, reliable production deployments.
• 8+ years of proven experience in statistics, AI, or ML.
• Hands-on expertise with Python, SQL, and Java, as well as modeling frameworks such as scikit-learn, PyTorch, and TensorFlow for large projects.
• Experience with data storage and processing tools such as Spark, Pandas, and Delta Lake, including troubleshooting large-scale software running in complex networks.
• Excellent verbal and written communication skills, with the ability to convey complex data insights to technical and non-technical stakeholders.
• An outstanding track record of successful lead projects involving the research and application of data science at scale.
• Experience with user retention modeling, LLMs, time-series forecasting, or operations research is a plus.

NVIDIA uses AI tools in its recruiting processes and is committed to fostering an inclusive work environment. The company is an equal opportunity employer.

Applications for this job will be accepted at least until June 26, 2026. This posting is for an existing vacancy.