Risk Analyst

Have you ever thought about what it takes to detect and prevent fraudulent activity in hundreds of millions of eCommerce transactions across the globe?

As a Risk Analyst in Buyer Risk Prevention (BRP), you will be responsible for analyzing terabytes of data to identify specific instances of risk, broader risk trends and points of customer friction.

Key Responsibilities:

• Perform complex data analysis to proactively generate actionable insights
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. within SQL and other BI tools
• Design and implement various visual dashboards in order to make insights available to team members, stakeholders and our customers
• 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
• 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

A Day in the Life:

1. Review instances of fraud and create mechanisms to stop them
2. Report on fraud trends and improve products
3. Create and maintain dashboards that detect and inform stakeholders (such as payment product owners) on how to stop fraud

About the Team:

Our team consists of Business Analysts, Data Scientists, Business Intelligence Engineers and Applied Scientist rolling under the core Buyer Risk Prevention Machine Learning Team.

Basic Qualifications:

• 1+ years of business or financial analysis experience
• Experience with SQL or ETL
• Experience defining requirements and using data and metrics to draw business insights

Preferred Qualifications:

• Bachelor's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or PhD
• 1+ years of professional work experience, or experience in SQL or other relational databases
• Knowledge of a scripting language (Python, R, etc.)