Data Scientist Amazon
Seattle, WA

Job Description

The Amazon Devices organization designs, produces and markets Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players and Echo Speakers, and is constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving the customer experience on existing platforms. The Devices Analytics team provides customer engagement support to the broader organization for Kindle, Fire, and Echo products - established and emerging countries, worldwide.

We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team.

Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, and predictive machine learning tools. This Data Scientist role is responsible for building quantitative systems and predictive models that are critical inputs to Amazon's financial and operational planning. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams.

In this role, you will be a technical expert with massive impact. You will take the lead on developing our forecasting technology for key Devices metrics. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs.

Key Performance Areas

* Implement statistical or machine learning methods to solve specific business problems.
* Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
* Directly contribute to development of modern automated forecasting systems
* Build customer-facing reporting tools to provide insights and metrics which track forecast performance and explain variance
* Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback