Principal Data Scientist - Cloud Gaming and AI

Responsibilities

• Provide Technical Leadership to the team of Data Scientists and Engineers working on global deployment at scale of GPU Compute services.
• Work with Leadership and Stakeholders to understand top level requirements, build a tech roadmap, design solutions and guide the team to deliver results.
• Acquire and apply domain knowledge of the product and platform to lead the design, implementation, and deployment of AI/ML based solutions for generating actionable insights and real-time prescriptive analytic pipelines to drive optimal outcomes for production services.
• Build and Deploy real time and scalable solutions for real time User Diagnostics, LLM Chatbot, dynamic Suspicious Activity Detection, User feedback based clustering and alerting and LLM based Actionable Insight Generation solutions for Engineering And Management.
• Improve productivity of the org by wrangling petabytes of data using statistical/AI/ML/LLM models to provide actionable and real time insights.
• Leverage pioneering Forecasting models and Constraint Optimization solvers to improve capacity management and deliver server efficiency and end-user latency.
• Leverage innovative ML/AI predictive models with explainability for User Retention/Churn and designing outreach campaigns.
• Build innovative multi-agent self-learning Harnesses for improving engineering productivity for analytics and deployments.
• What we need to see:
• Master's/PhD or equivalent experience in Data Science, Statistics, Mathematics, Physics, Operations Research or related quantitative field
• 15+ years of software experience for large-scale and reliable production deployments and 8+ years of proven experience in Statistics/AI/ML
• Hands-on expertise in programming languages like Python, SQL, Java and modeling frameworks like Scikit-learn, Pytorch, TensorFlow for large projects.
• Experience with common tools for data storage and processing (e.g. Spark, Pandas, Delta Lake) including drilling into problems of running large scale software in a big network.
• Excellent verbal and written communication skills to convey rich data insights to non-Technical and Technical Stakeholders.
• An outstanding track record of successful past projects, as a lead, related to the research and application of data science at scale.
• Experience of User Retention Modeling, LLMs, Time Series Forecasting or Operations Research is a plus.
• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 379,500 USD. You will also be eligible for equity and benefits .
• Applications for this job will be accepted at least until June 26, 2026. This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.

Additional Information

Join the NVIDIA GeForce NOW cloud team that allows users to play high-quality PC games on various devices, without the need for a dedicated gaming PC or console. NVIDIA's GeForce NOW service is built on top of our GPU technology, including our proprietary GPU architectures and software optimizations allowing efficient and high-quality experience even at high resolutions and fps and at industry leading low latencies. Our team is building the Diagnostic, Prescriptive and AI-augmented Analytics solutions that encompass processing, visualization, anomaly detection, root cause and predictive modeling for the benefit of millions of our end users. Our active projects include real-time forecasting of demand, constraint-optimized capacity allocation, dynamic prescriptions per session, Customer Onboarding and Voice of Customer Analytics, targeted Customer Outreach campaigns based on Customer Retention modeling, effective personalized diagnostic recommendations, LLM Chatbot. You will wield the power of Data and AI to help globally deliver a best-in-class cloud computing/streaming performance and experience. Our technology stack relies on industry standard components and tools (Python, R, Pandas, JupyterLab, Spark, SQL, Databricks, MLFlow, Delta Lake, Grafana, Kibana, Kubeflow, Elyra, Kubernetes, Gitlab, CI/CD, MLOps, Kafka, SQS, Kubernetes)

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