Fraud Risk Analyst: Data-Driven Fraud Prevention & Insights

U.S. Bank; Tempe (AZ); On-site; USD 93,000 - 109,000; Full time

Benefits offered by this job

Healthcare (medical, dental, vision)

Paid vacation

401(k)

Job summary

U.S. Bank is hiring a Fraud Risk Analyst for the Quantitative Fraud Strategy team in Tempe, AZ.

You will support fraud prevention, detection, and rule management through data analysis using SAS, SQL, or Python, and monitor performance across digital channels and money movement products. The role requires strong analytical abilities, curiosity about fraud trends, and the ability to translate complex findings into actionable recommendations while collaborating with risk management, technology, and

Qualifications

• Bachelor's degree or equivalent work experience.
• Typically more than five years of applicable experience.
• Experience with analytical tools such as SAS, SQL, or Python.
• Knowledge of financial services products, systems, and data, especially in fraud domain.

Responsibilities

• Analyze fraud rule performance, alert outcomes, customer impacts, and loss trends to assess effectiveness and identify improvement opportunities.
• Leverage large datasets to identify emerging fraud patterns and performance shifts.
• Develop data-driven recommendations balancing fraud risk and customer experience.
• Conduct root-cause analysis on fraud events and operational trends to support rule improvements.
• Translate findings into clear summaries for management reviews and decisions.
• Collaborate with cross-functional teams to validate findings and align with governance.

Skills

Analytical thinking

Effective communication

Problem solving

Cross-functional collaboration

Education

Bachelor’s degree or equivalent

Master’s degree a plus

Tools

SAS

SQL

Python

Microsoft Excel

Job description

U.S. Bank is hiring a Fraud Risk Analyst for the Quantitative Fraud Strategy team in Tempe, AZ.

You will support fraud prevention, detection, and rule management through data analysis using SAS, SQL, or Python, and monitor performance across digital channels and money movement products. The role requires strong analytical abilities, curiosity about fraud trends, and the ability to translate complex findings into actionable recommendations while collaborating with risk management, technology, and