Principal Data Scientist - Cloud Gaming and AI

Description

The company runs GeForce NOW, a cloud gaming service that lets users play high-quality PC games on a range of devices without owning a gaming PC or console. The service runs on the company's own GPU technology, including proprietary GPU architectures and software optimizations, to deliver high resolutions, high frame rates and industry-leading low latency.

The team builds diagnostic, prescriptive and AI-augmented analytics covering processing, visualization, anomaly detection, root cause analysis and predictive modeling. Current projects include real-time demand forecasting, constraint-optimized capacity allocation, per-session dynamic prescriptions, customer onboarding and voice-of-customer analytics, targeted retention outreach campaigns, personalized diagnostic recommendations and an LLM chatbot. The work serves millions of end users.

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

Responsibilities

• Lead a team of data scientists and engineers deploying GPU compute services globally at scale.
• Work with leadership and stakeholders to clarify top-level requirements, then set the technical roadmap, design solutions and guide the team to results.
• Build a working knowledge of the product and platform, and lead the design, implementation and deployment of AI and ML solutions that produce actionable insights and real-time prescriptive analytics pipelines for production services.
• Build and deploy scalable, real-time solutions for user diagnostics, an LLM chatbot, dynamic suspicious activity detection, clustering and alerting from user feedback, and LLM-based insight generation for engineering and management.
• Process petabytes of data with statistical, AI, ML and LLM models to deliver actionable, real-time insights that raise organizational productivity.
• Use forecasting models and constraint optimization solvers to improve capacity management, server efficiency and end-user latency.
• Build explainable ML and AI models for user retention and churn, and design outreach campaigns around them.
• Build multi-agent, self-learning harnesses that improve engineering productivity in analytics and deployments.

Requirements

• Master's or PhD, or equivalent experience, in data science, statistics, mathematics, physics, operations research or a related quantitative field.
• 15+ years of software experience building large-scale, reliable production systems, including 8+ years of proven experience in statistics, AI or ML.
• Hands-on skill in Python, SQL and Java, and in modeling frameworks such as Scikit-learn, PyTorch and TensorFlow, on large projects.
• Experience with data storage and processing tools such as Spark, Pandas and Delta Lake, including diagnosing problems in large-scale software running on a large network.
• Clear verbal and written communication, able to explain data insights to both technical and non-technical stakeholders.
• A strong record of leading data science projects at scale, from research through application.
• Experience with user retention modeling, LLMs, time series forecasting or operations research is a plus.

Conditions

Base salary is set by location, experience and other objective job-related factors, within an expected range of 248,000 USD to 379,500 USD.

Applications are accepted at least until November 3, 2026.

This posting is for an existing vacancy.

The company uses AI tools in its recruiting process.

The company is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by law.

Benefits

• Competitive salary and a generous benefits package.