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Amazon Risk Analyst II, Payment Risk Mining Analytics in San Jose, Costa Rica

Description

Have you ever thought about what it takes to detect and prevent fraudulent activity in 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 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.

Key job responsibilities

Risk Analyst II will own analytical deep dives to identify emerging fraud patterns and communicate findings in written to ML teams, Program Managers and other cross-functional partners. The successful candidate will demonstrate an ability to thrive in a fast-paced and challenging environment and partner with stakeholders across multiple domains.

A day in the life

-Provide time sensitive analytics to partner teams

-Deep Dive on emerging fraud patterns using SQL on large datasets

-Identify root cause and work with partners such as ML teams to develop sustainable solutions

-Automate tasks using dashboards

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

San Jose, CRI

Basic Qualifications

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

  • Advanced SQL experience

  • Bachelor's degree or equivalent

  • 4+ years analytical field experience

  • Experience with reporting and Data Visualization tools such as Quicksight / Tableau / Power BI or other BI packages

Preferred Qualifications

  • Experience scripting for automation (e.g., Python, Perl, Ruby)

  • Statistical Analysis Experience

  • Machine Learning Experience

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