Risk Manager I, Risk Mining

Overview

The Seller Partner Identity Verification team is responsible for knowing who we’re doing business with. We do this by applying a thorough verification process at key points during the seller or vendor lifecycle as well as deploying bad actor detection and enforcement. We organize this work into five programs aligned with different stages of the seller and vendor journeys. Within SPIV, the Registration and Verification team seeks to stop bad actors from gaining access to our store by providing proactive and customized registration and verification services. Our mission is that we build trust by protecting our customers, selling partners, and our store from bad actors.

Key job responsibilities

• Conduct investigations into allegations of organized fraud or abuse on and off the Amazon platform.
• Use a combination of manual and automated tools to obtain information & reporting bugs and tool improvement ideas.
• Take appropriate action to identify and help minimize the risk posed by fraud or abuse patterns and trends.
• Perform dive-deep into the tasks reported through trouble tickets, checking registration history of sellers etc.
• Perform dive-deep by taking samples of sellers from the queues in case anomalies or unexpected queue spikes are observed
• Flag new risk attributes to automation team and suggest changes in SOP if the process requires enhancement to close loop holes for bad actors.

Basic Qualifications

• Chinese language proficiency required
• Bachelor's degree or equivalent
• 2+ years of compliance program management, legal, governance, audit, risk/loss prevention, or equivalent experience
• 2+ years of banking industry experience with specialization in fraud risk management
• Proficiency in SQL and Microsoft Excel
• Ability to organize and manage multiple tasks simultaneously, and to facilitate multiple discussions.
• Self-driven & motivated individual with demonstrated ability to perform well independently and as part of a team

Preferred Qualifications

• Bachelor’s Degree in any quantitative discipline such as Computer Science, Statistics, Operational Research or Engineering
• Experience working in Analytics / Business Intelligence environment
• Experience/knowledge of advanced machine learning techniques such as GBM, random forest, etc.

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