Description de l'offre
Position location flexible (Seattle, San Diego, Bay Area)
How can we improve the customer experience by tailoring what we display on our pages based on available data? How do we build various data models that helps us innovate different ways to enhance customer experience? What is the relationship to what the customer actually does on the site vs., what they actually buy? How do we do all of this without asking the customer a single question? Sounds fun?
The answers to these questions and others like them are core to helping Amazon Kindle business in many ways, including customer experience, recommendations, and others. Amazon Kindle is a revolutionary reading device, the #1 best-selling product on all of Amazon, and one of the most innovative and fast growing businesses at Amazon. Our team develops cutting edge Kindle applications for personal computers and mobile devices, which blend seamlessly into the Kindle suit of services and are at the forefront of reinventing our customer’s reading experience. The Digital store team in Kindle Organization is charged with creating rich experiences that enhance what the customer sees and experiences on our storefront pages.
Using Amazon’s large-scale computing resources to build models describing best suited recommendations and work with domain experts and engineers to help turn those models into production solutions. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the Amazon Kindle business. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.
· MS. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· At least 5+ years of hands-on experience in predictive modeling and analysis
· At least 5+ years algorithm development experience
· At least 2+ years with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language