NVIDIA

Senior Data Scientist, Cloud Gaming

NVIDIA

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $152,000 - $230,000 per year

Job Level

Senior

Tech Stack

ApacheCloudGrafanaPythonSparkSQL

About the role

  • Build and deploy scalable ML/AI models to optimize the demand forecasting, capacity allocation and user specific feature-engineering for the real time cloud gaming service.
  • Build improvements to real-time prescriptive scheduling pipelines to maximize capacity utilization and user retention.
  • Acquire and apply domain knowledge of the product and software stack to identify and drive the resolution of data inconsistencies and improve model performance.
  • Develop re-useable framework deployments for data ingestion, processing and analysis.
  • Identify, analyze, and interpret trends or patterns in complex data sets using supervised and unsupervised learning techniques.
  • Improve productivity of the org by wrangling petabytes of data to provide actionable insights to business and engineering.
  • Work with a variety of stakeholders to understand requirements, design solutions, and guide the team to deliver results.
  • Leverage agentic AI to deliver best-in-class programming solutions.

Requirements

  • BS/MS or equivalent experience with 5+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, or related quantitative fields.
  • Strong background knowledge and practical experience in probability, statistics, and AI/ML.
  • An outstanding track record of past projects related to the research and application of data science.
  • Strong coding skills, including the ability to write readable, testable, maintainable, and extensible code (primarily Python)
  • Experience with common tools for data storage and processing, including drilling into problems of running large-scale software in a big network.
  • Strong experience in data cleaning, aggregation, transformation, and extraction.
  • Good interpersonal and presentation skills in working with multiple partners.
  • Experience with time series analysis is a plus.
  • Experience in active ML production pipelines is a plus (MLflow, KubeFlow).