Java Programming, Python Programming, C++, SQL, R Programming
Job summary
How can we create a rich, data-driven shopping experience on Amazon? How do we build data models that helps us innovate different ways to enhance customer experience? How do we combine the world's greatest online shopping dataset with Amazon's computing power to create models that deeply understand our customers?
Recommendations at Amazon is a way to help customers discover products. Our team's stated mission is to grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations. We strive to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day.
Using Amazon’s large-scale computing resources you will ask research questions about customer behavior, build models to generate recommendations, and run these models directly on the retail website. 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 retail business and you will measure the impact using scientific tools. 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.
Key job responsibilities
BASIC QUALIFICATIONS
PREFERRED QUALIFICATIONS
Amazon Science examines the company’s approach to scientific innovation. Amazon believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields.
Toronto, ON, Canada
2-4 year
Arlington, VA, USA
2-4 year
Pasadena, CA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Washington D.C., DC, USA
2-4 year
Vancouver, BC, Canada
2-4 year
Santa Clara, CA, USA
0-2 year