Hundreds of millions of customers, billions of transactions, petabytes of data… How to use the world's richest collection of e-commerce data to provide superior value and better paying experience to customers ? The Amazon Payments Team manages all Amazon branded payment offerings globally. These offerings are growing rapidly and we are continuously adding new market-leading features and launching new products. Amazon.com has a culture of data-driven decision-making and demands business intelligence that is timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities.
Our team of high caliber software developers, data scientists, statisticians and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between click through rate, approval rates and lifetime value. In order to accomplish this we leverage the wealth of Amazon's information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon's technological infrastructure to display the right offerings in real time.
We are seeking a strong, business savvy Business Intelligence Engineer to tackle the growing complexity of our international business by developing models, data-driven insights, and frameworks to better serve our customers around the world.
* Building and refining models to identify opportunities and key criteria to drive selection strategy * Conducting deep dive analyses of business problems and formulate conclusions and recommendations to be presented to senior leadership. * Producing written recommendations and insights for key stakeholders that will help shape effective metric development and reporting. * Building simple and effective infrastructure tools with scalability top of mind. * Simplifying and automating reporting, audits, and other data-driven activities; build solutions to have maximum scale and self-service ability by stakeholders. * Improving back-end data sources for increased accuracy and simplicity. * Recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. * Supporting business with time-critical tactical data analyses. * Understanding a broad range of Amazon's data resources and know how, when, and which to use and which not to use.
Amazon is a company operating a marketplace for consumers, sellers, and content creators.