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DESCRIPTION

Are you passionate about working with Amazon-scale data, analytics, and data science? Do you love bringing data together from diverse systems and sources and working on critical analytics problems for understanding customer behavior and generating actionable insights? Does the idea of partnering with a team of highly experienced machine-learning scientists and engineers excite you? Science and Analytics team is looking for an experience, self-driven business-intelligence engineer to help us synthesize data into knowledge across a large number of businesses to help independent authors bring their creativity to customers, detect fraudulent and abusive behavior, and democratize content creation in an safe, efficient, and exciting way. Our team has mature areas and green-field opportunities. We offer technical autonomy, value end-to-end ownership, and have a strong customer-focused culture.

Come join us as we revolutionize the book industry and deliver an amazing experience to our authors and readers.

Key job responsibilities
As a Business Intelligence Engineer at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with massive-scale data and providing analytic support to scientists, product managers, engineers using these data. You will utilize your deep expertise in business analysis, metrics, reporting, and analytic tooling/languages like SQL, Excel, and others, to translate the data into meaningful insights. You will have ownership of the insights you are building for the business, and will play an integral role in tactical decision-making for critical risk areas.

About the team
Minerva is a cross-functional team of highly experienced scientists, data engineers, and software engineers with a critical business mission making revolutionary leaps forward using massive-scale data with advanced analytics and machine learning and helping democratize the publishing industry. We build science-based systems for marketing and content-discovery for indie authors, fraud/abuse, and content risk. We also use science to optimize manufacturing, fulfillment, and quality processes for our Print On Demand (POD) business.