Analyst, Fraud and Credit Risk Management

About the role

This role supports enterprise fraud risk management by analyzing data to identify emerging fraud patterns and improve the performance of automated fraud decisioning. It involves applying statistical and quantitative methods to measure the effectiveness of fraud rules and strategies across application/identity fraud, payment and transaction fraud, and other fraud programs as needed. The role requires managing large datasets from multiple internal and third-party sources and collaborating with cross-functional teams to turn analysis into strategy. Success is measured by the accuracy and timeliness of fraud reporting and the effectiveness of the strategies that reporting informs, balancing fraud loss reduction against approval rates and customer friction. The work directly influences organization-wide fraud exposure and is presented regularly to fraud and credit risk leadership to guide business decisions.

Responsibilities

• Design, build, and maintain program-level fraud reporting: KPIs, scorecards, dashboards, and recurring readouts covering fraud loss, detection performance, and customer impact
• Monitor and measure fraud decision engine performance and drive tuning recommendations
• Apply segmentation and statistical analysis (trend, regression, cohort, champion/challenger and A/B test readouts) to size fraud opportunities and quantify the impact of strategy changes
• Extract, process, and transform data from multiple sources — application, payment and transaction, device, and third-party identity and fraud vendor data — into analysis-ready datasets
• Evaluate new data sources and analytic products from external vendors, support proof-of-concept testing, and document findings for stakeholders
• Conduct fraud loss forecasting and exposure analysis, quantifying tradeoffs between fraud loss, approval rates, and customer experience

Qualifications

Education:

• Bachelor's degree plus 2 years of related work experience OR combination of education and experience deemed equivalent (preferred areas of study: Finance, Economics, Mathematics, Industrial Engineering, Statistics or related degree)

Required Work Experience:

• Statistical Analysis
• Data Analysis and Extraction
• Intermediate to advanced Excel
• SQL
• Strategic Thinking
• Project Management

Preferred Experience:

• 2+ years experience in a quantitative analytical function
• Python
• Power BI
• Streamlit
• Snowflake
• AI – Claude or ChatGPT
• Predictive Modeling
• Regression Analysis

At least 18 years of age. Legally authorized to work in the United States.

Pay

• Base Pay Range: $76,100 - $137,300
• Corporate Bonus Target: 10%

Benefits

• Medical, dental and vision insurance
• Flexible spending account
• 401(k)
• Employee stock grants
• Employee stock purchase plan
• Paid time off and up to 12 paid holidays (about 4 weeks for new full-time employees annually)
• Paid parental and family leave
• Family building benefits, back-up care, enhanced family support, childcare subsidy
• Tuition assistance and college coaching
• Short- and long-term disability
• Voluntary AD&D coverage, accident coverage, life insurance, disability insurance, and long-term care insurance
• Mobile service and home internet discounts
• Pet insurance
• Commuter and transit programs