Fraud Advanced Analytics and Insights

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

NOTE:
Advanced SAS programming and advanced analytics experience is required for this position.

NOTE:
This position is not eligible for current or future visa sponsorship.

Job Description

The Fraud Risk Analyst applies advanced analytics to evaluate fraud strategies, fraud controls, authentication solutions, and fraud-prevention capabilities across deposits, payments, digital channels, and the account lifecycle. The role focuses on identifying fraud risk, quantifying business impact, measuring control effectiveness, and developing data-driven recommendations that influence fraud strategy and business decisions.

This is an analytics-focused position. The successful candidate will independently perform data analysis from problem definition through recommendation development. The role is not primarily focused on reporting, dashboard production, or routine data requests. Success in this position requires identifying business problems, developing analytical approaches, quantifying business impact, and influencing fraud strategy through data-driven recommendations.

The analyst works with internal stakeholders and external partners to evaluate tools, data sources, and capabilities that enhance fraud detection and decisioning. By translating complex analytical findings into executive-ready insights and cost-benefit assessments, the role informs strategic decision-making while balancing fraud risk reduction, customer experience, operational efficiency, and financial impact.

Key Responsibilities

• Analyze complex, multi-channel fraud trends and performance data to identify emerging risks, root causes, and opportunities for fraud loss reduction across the account lifecycle.
• Independently develop analytical approaches and recommendations that address fraud risks, control effectiveness, and business priorities.
• Develop data-driven insights and strategic recommendations that strengthen fraud prevention and detection while balancing fraud risk, customer experience, and operational efficiency.
• Evaluate fraud controls, authentication strategies, fraud-detection rules, and fraud-prevention capabilities through quantitative analysis to identify performance gaps and optimization opportunities.
• Measure and quantify business impact, including fraud loss reduction opportunities, customer experience outcomes, operational efficiency improvements, and return on investment.
• Develop business cases and cost-benefit analyses that support fraud strategy, prioritization, and investment decisions.
• Translate complex analytical findings into executive-ready insights and recommendations that influence fraud strategy and business decisions.
• Collaborate with internal stakeholders and external partners to evaluate fraud tools, data sources, and capabilities that enhance fraud detection and decisioning.

Basic Qualifications

• Bachelor's degree or equivalent work experience.
• Six or more years of relevant analytics experience.

Required Analytics Experience

Six or more years of advanced SAS programming and analytics experience is required. Experience evaluating fraud strategies, fraud controls, authentication solutions, and fraud-prevention capabilities through quantitative analysis is strongly preferred. Candidates should be capable of independently performing analytics from problem definition through recommendation development and translating findings into business recommendations and executive-ready insights.

SQL experience is strongly preferred.

Python experience is preferred.

Preferred Skills/Experience

• Bachelor's degree in Business, Finance, Computer Science, Business Analytics, Statistics, Mathematics,…