Analyst, Fraud and Credit Risk Management

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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. 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

Requirements

• Bachelor’s degree plus 2 years of related work experience OR combination of education and experience deemed equivalent
• Acceptable areas of study include Finance, Economics, Mathematics, Industrial Engineering, Statistics or related degree (preferred)
• Statistical Analysis
• Data Analysis and Extraction
• Intermediate to advanced Excel
• SQL
• Strategic Thinking
• Project Management
• At least 18 years of age
• Legally authorized to work in the United States

Qualifications

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

Pay

Base Pay Range: $76,100 - $137,300. The successful candidate’s actual pay will be based on work location, qualifications, and experience. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance, set at a percentage of the employee’s eligible earnings in the prior year (e.g., 10% target). Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance.

Benefits

• Medical, dental, and vision insurance
• Flexible spending account
• 401(k) with company match
• Annual stock grant and employee stock purchase plan
• Paid time off (up to 4 weeks for new full-time employees, ~2.5 weeks for new part-time employees) plus up to 12 paid holidays annually
• Paid parental and family leave
• Family building benefits
• Back-up care and enhanced family support
• Childcare subsidy
• Tuition assistance and college coaching
• Short- and long-term disability
• Voluntary AD&D, accident, life, and long-term care insurance
• Mobile service and home internet discounts
• Pet insurance
• Commuter and transit programs