Amazon's Intelligent Cloud Control Group in Berlin is looking for an experienced Applied Scientist to join our CloudTune Applied Research team. The team develops large-scale machine learning implementations that will revolutionize the way people interact with the Internet. We are building an Intelligent Cloud Control System that enables Amazon businesses (Retail, Amazon Video, Kindle, and more) continue innovating in the cloud.
As a scientist in the CloudTune team you'll partner with technology and business teams to build new services that surprise and delight our customers. We develop sophisticated algorithms that involve learning from large amounts of past data, such as actual sales, website traffic, merchandising activities, promotions, similar products and product attributes, in order to forecast the demand for our compute infrastructure. These forecasts are used to determine the level of investment in capital expenditures, promotional activity, engineering efficiency projects and determining financial performance.
You will work on mathematical problems with a large element of unpredictability. You will analyze and process large amounts of data, develop new sophisticated 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's businesses.
· 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 mathematical models to represent demand forecasting at various levels.
· Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
· Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.
We're looking for top scientists capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.