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Risk Mining Analyst II, Account Integrity
Risk Mining Analyst II, Account Integrity-March 2024
San Jose
Mar 28, 2026
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About Risk Mining Analyst II, Account Integrity

  Description

  Amazon’s Account Integrity team (AIT) within the Selling Partner Support organization is looking for a passionate, results-oriented Risk Mining Analyst (similar to business analyst) to leverage data, detect anomalies and prevent bad actors for harming our genuine customers. The incumbent will lead one of the core verticals of Risk Mining with AIT. The AIT team owns designing and building high performance software systems using machine learning that identify and prevent fraudulent activity and maintain high trust levels with our customers. Fraud and abuse prevention is a real-money game where our software and analytics teams strive to outsmart those who attempt to defraud Amazon and our customers.

  As a Business Analyst for Risk Mining in the Account Integrity group, you will be responsible for analyzing large data sets in partnership with product managers, scientists, and engineers, drive root cause analysis of ever changing bad actor behaviours and deploy rules that will prevent bad actors from gaining access to Amazon's platform

  Key job responsibilities

  Create, maintain, and improve data sets, pipelines and reporting to track and manage important KPIs and goals in the Account Integrity space

  Analyze complex customer trends to identify patterns, develop attritbutes that clearly articulate those pattern and incorporate those 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 alarm systems, derive actionable insights and guide product strategy for stakeholders and leadership

  Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. within SQL and other BI tools

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

  Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format

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

  A day in the life

  Review instances of bad actor account activity and create mechanisms to stop them

  Report on fraud and abuse trends and improve products

  Create and maintain dashboards that detect and inform stakeholders (such as downstream payment and abuse product owners) on how to stop fraud

  Participate and lead process improvement initiatives across account integrity teams

  Develop rules to mitigate bad actor activity

  About the team

  Our team consists of Business Analysts and Risk Mining specialists rolle up under the Account integrity Machine Learning Team. We evaluate instances of organized bad actor account take over and creation of fraudulent accounts on Amazon . We collaborate closely across multiple functions in order to mitigate these attacks through various short and long term solutions.

  We are open to hiring candidates to work out of one of the following locations:

  San Jose, CRI

  Basic Qualifications

  3+ years of tax, risk, finance or a related analytical field experience

  5+ years of Excel (including VBA, pivot tables, array functions, power pivots, etc.) and data visualization tools such as Tableau, Amazon Quicksight

  Bachelor's degree or equivalent

  Experience with SQL. Should be able to independently write and audit queries for data extraction, auto queries for building alarms etc.

  Experience defining requirements and using data and metrics to draw business insights

  Experience with data pipelines, storage requirements and extraction

  Preferred Qualifications

  Bachelor’s Degree in any quantitative discipline such as Statistics, Mathematics or Economics.

  5+ years of experience working in Analytics / Business Intelligence environment.

  Demonstrated experience using scripting languages like R or Python.

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