Data Scientist


Job Overview


Are you passionate about leveraging data to deliver actionable insight that impacts daily business decisions for Amazon? Does the prospect of dealing with massive volume of data excite you? Are you interested in working on Data Science, believing every customer should have a tailored and personalized experience?

We get millions of customer visit each day, shopping for thousands of products. We provide highly scalable, personalized shopping experiences for Amazon devices, accessories, and services for all channels, including voice, which will change the way people shop on Amazon. You will have an opportunity to develop data driven solutions and drive business impacts. You will play a key role to drive end-to-end solutions from understanding our business and business requirements, identifying opportunities from a large amount of historical data, building prototypes and exploring conceptually new solutions, running online experiments, to working with partner teams for prod deployment. You will collaborate closely with engineering peers as well as business stakeholders. You will play a key role in redefining shopping experience for Amazon Devices.

You will work closely with product managers and software developers to identify and solve real-world customer problems and business opportunities. You will have the opportunity to interact with data scientist throughout the company to determine the best practices for model building, prototyping, developing and deploying software solutions. You will have complete ownership to define new shopping experiences and drive innovation with the latest machine learning skills. This is a high visibility and fast-paced environment where you will make a direct impact on the customer experience and the bottom line of the company.

Job responsibilities
· Interact with product, and engineering teams to understand business requirements and development processes
· Frame business problems into scalable solutions
· Process and analyze sales data; gather additional data sources that would improve model performance
· Prototype models by R/Python and work with software teams to take the models to production.
· Create and track accuracy and performance metrics (both technical and business metrics)

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