Have you ever thought about what it takes to detect and prevent fraudulent activity among hundreds of millions of eCommerce transactions across the globe? What would you do to increase trust in an online marketplace where millions of buyers and sellers transact? How would you build systems that evolve over time to proactively identify and neutralize new and emerging fraud threats?

Our mission in Buyer Risk Prevention (BRP) is to make Amazon.com the safest place to transact online. BRP safeguards every financial transaction across all Amazon sites, while striving to ensure that these efforts are transparent to our legitimate customers. As such, BRP designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon.com.

As a Risk Analyst in BRP, you will be responsible for analyzing terabytes of data and evaluating system process to identify specific instances of risk, developing scalable and automated solutions to help Scientists, Product and Operations to mitigate organized fraud attacks.

Key job responsibilities
Design, develop, and maintain metrics, reports, analyses, dashboards using SQL, Python and other BI tools;

Design and implement various visual dashboards via Quick-sight to provide actionable insights to team members, stakeholders and our customers;

Design and develop ETL pipelines to automate business or science reports/monitors;

Support cross-functional teams on the day-to-day execution of projects and initiatives;

Preparing and delivering business reviews to the senior management team regarding progress and roadblocks;

Communicate complex analysis and insights to stakeholders and business leaders, both verbally and in writing;

About the team
Our team consists of Risk Analysts, Data Scientists, Business Intelligence Engineers and Applied Scientist rolling under the core Buyer Risk Prevention Machine Learning Team. We evaluate instances of organized buyer fraud attacks on Amazon platform WW across various payment methods. We collaborate closely across multiple functions in order to mitigate these attacks through various short and long term solutions.