Risk Analyst, Account Integrity

About Amazon's Account Integrity Team

Amazon’s Account Integrity team (AIT) within the Selling Partner Support organization is actively seeking a passionate, results-oriented Risk Analyst. This role is crucial for leveraging data, detecting anomalies, and preventing malicious actors from harming our genuine customers. The incumbent will be at the forefront of one of the core verticals of Risk Mining within AIT. Our team is dedicated to designing and building high-performance software systems that utilize machine learning to identify and prevent fraudulent activity, thereby maintaining high trust levels with our customers. Fraud and abuse prevention at Amazon is a high-stakes game where our software and analytics teams constantly strive to outsmart those who attempt to defraud Amazon and its customers.

Role and Responsibilities of a Risk Analyst, Account Integrity

As a Business Analyst for Risk Mining in the Account Integrity group, you will be instrumental in analyzing large data sets, working closely with product managers, scientists, and engineers. A key aspect of this role involves driving root cause analysis of ever-changing bad actor behaviors and deploying rules to prevent these bad actors from accessing Amazon's platform.

Key Job Responsibilities

• Create, maintain, and improve data sets, pipelines, and reporting mechanisms to effectively track and manage important KPIs and goals within the Account Integrity domain.
• Analyze complex customer trends to identify patterns, develop attributes that clearly articulate those patterns, and incorporate these attributes into static rules for automated deployment in our account creation pipeline.
• Apply your expertise in quantitative analysis, data visualization, and data-mining to design robust alarm systems, derive actionable insights, and guide product strategy for stakeholders and leadership.
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards, primarily utilizing SQL and other BI tools.
• Support cross-functional teams in the day-to-day execution of various projects and initiatives.
• Enable effective decision-making by efficiently retrieving and aggregating data from multiple sources, compiling it into a digestible and actionable format.
• Communicate complex analysis and insights to stakeholders and business leaders, both verbally and in writing, ensuring clarity and impact.

A Day in the Life

• Review instances of bad actor account activity and develop rules for short-term mitigation, alongside creating mechanisms for long-term prevention.
• Report on fraud and abuse trends, leveraging this information to provide critical inputs for product development.
• Create and maintain dashboards that detect and inform stakeholders (including downstream payment and abuse product owners) on how to stop fraud and abuse through early-stage detection of bad actor behavior.
• Participate in and lead process improvement initiatives across various account integrity teams.
• Develop rules specifically designed to mitigate bad actor activity.
• Create long-term solutions, potentially leveraging Generative AI.

About The Team

Our team comprises dedicated Risk Managers, Risk Analysts, and Risk Mining Specialists within the Account Integrity Machine Learning Team. We meticulously evaluate instances of organized bad actor account takeovers and the creation of fraudulent accounts on Amazon. We foster close collaboration across multiple functions to mitigate these attacks through a combination of short-term and long-term solutions.

This role provides crucial support to existing teams based in Costa Rica (CR), India (IN), and the United States (US), and delivers support to customers worldwide.

Basic Qualifications

• 4+ years of experience in compliance program management, legal, governance, audit, risk/loss prevention, or equivalent.
• Bachelor's degree or equivalent practical experience.
• Demonstrated experience handling confidential information with discretion.
• Proficiency with SQL and Excel.

Preferred Qualifications

• 3+ years of experience in program requirements definition and leveraging data and metrics to drive improvements.
• Demonstrated experience using scripting languages such as R or Python.
• Basic understanding of Machine Learning concepts and the ability to leverage Generative AI tools.

Key skills/competency

• Data Analysis
• Risk Management
• Fraud Detection
• SQL
• Excel
• KPI Tracking
• Root Cause Analysis
• Business Intelligence (BI) Tools
• Stakeholder Communication
• Machine Learning (basic)