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Nvidia Senior Data Processing Platform Engineer United States, Texas
Optimize distributed computing infrastructure by analyzing cost and right sizing for latency and performance. Identify KPIs and instrument metrics tracking for dashboards and alerting. Enhancing and maintaining a robust scale,...
Working closely with architecture, hardware and driver teams through the product development lifecycle of computing and graphics processors, as well as compute products. Responsible for crafting software tools and infrastructure...
Manage and optimize transportation data in our TMS (e.g., SAP TM, Oracle OTM), ensuring accuracy across rates, lanes, and carriers. Monitor and validate incoming logistics data from EDI 214, 210,...
Bachelor's degree in Mechanical or Industrial Engineering, related discipline, or equivalent practical experience. 3 years of experience in mission critical facility design and construction environments. 3 years of experience in...
Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing and launching software products and 3 years of experience with software design...
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 4 years of experience using analytics to solve product or business problems, coding (e.g., Python,...
Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 3 years of work experience using analytics to solve product or business problems,...
Optimize distributed computing infrastructure by analyzing cost and right sizing for latency and performance. Identify KPIs and instrument metrics tracking for dashboards and alerting. Enhancing and maintaining a robust scale,...
Data Scientists are responsible for analyzing and interpreting large and complex datasets to uncover insights that inform business decisions and drive innovation. They use a combination of statistical and machine learning techniques, as well as programming languages such as Python and R, to extract, clean, and transform data. They also use tools such as SQL, Hadoop and Spark to work with large datasets and perform data analysis.
Data Scientists work closely with cross-functional teams, such as product managers, marketing and operations, to understand their specific data needs and provide them with insights to make informed decisions. They also collaborate with data engineers to build and maintain the infrastructure necessary for data analysis. They also use data visualization tools such as Tableau and Power BI to create interactive dashboards and reports to communicate data insights clearly and effectively to non-technical stakeholders.