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As a Senior Scientist in CloudTune, you will work with other scientists, software engineers, data engineers, and product managers on a variety of important applied machine learning problems in the area of time series modeling. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.Key job responsibilities
• Process and analyze large data sets, mining additional data sources as needed
• Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures
• Build statistical models and drive scalable solutions for multi-year capacity demand forecasting horizons
• Prototype these models by using high-level modeling languages such as R or Python
• Create, enhance, and maintain technical documentation, and present to other scientists and business leadersSeattle, WA, USA
- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 7+ years of building machine learning models or developing algorithms for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field
- 7+ years of industry or academic research experience
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