Data Scientist Amazon
Seattle, WA

Job Description

Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times?

These are among the most important questions at Amazon today. The Topline Forecast team in the Supply Chain Optimization Technologies (SCOT) organization is dedicated to answering these questions using statistical and machine learning methods. We are a diversely skilled and cross-functional software team which develops cutting edge scientific pipelines using native AWS tools and services to build accurate and automated predictive models. Our models are relied upon to provide forecasting insights to business leaders at the most senior levels throughout the company. We are looking for a talented, driven, and analytical researcher to help us answer these (and many more) questions.

This Data Scientist role is responsible for building quantitative systems and predictive models that generate multi-billion dollar predictions for Amazon's consumer business 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 contribute towards the development of production software systems, and possesses strong communication skills to effectively interface between technical and business teams.

As a Data Scientist on the Topline team, you will collaborate directly with economists, statisticians, and machine learning scientists to produce modeling solutions, you will partner with software developers and data engineers to build automated production systems, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business.

Key Responsibilities

* 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 the design and 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