Fraud Strategy Data Analyst: Enterprise Analytics

Usbank; Minneapolis (MN); On-site; USD 108,000 - 128,000; Full time

Benefits offered by this job

Healthcare benefits

Paid vacation

Holiday opportunities

401(k) retirement plan

Parental leave

Sick leave

Job summary

U.S. Bank is seeking a Fraud Strategy Data Analyst to deliver enterprise-level analytics across deposits, digital, payments, and account lifecycle. You will translate complex data into decision-ready insights to optimize fraud controls and business outcomes.

The role partners with Fraud Strategy, Risk, Operations, Digital, Technology, and AI/ML teams, applying rigorous measurement frameworks while driving scalable analytics and executive-level reporting.

Qualifications

• Bachelor’s degree or equivalent work experience
• Typically more than eight years of applicable experience

Responsibilities

• Leverage advanced technical proficiency in SAS/SQL/Python, and related analytical tools to extract, transform, and analyze large-scale fraud data, delivering scalable, data-driven insights that support fraud decisioning, tradeoff analysis, performance measurement, and strategic business decision-making.
• Analyze enterprise fraud performance across deposits, digital, payments, authentication, and account lifecycle domains to identify material loss drivers, customer friction, operational impacts, emerging risks, and opportunities to improve fraud outcomes.
• Evaluate fraud decisioning performance, alert effectiveness, decision outcomes, false positive rates, workflow execution, and queue dynamics to identify performance gaps, inefficiencies, and optimization opportunities.
• Assess end-to-end fraud operations, including alert lifecycle performance, queue throughput, review capacity, case-handling efficiency, and workload distribution to improve operational effectiveness and scalability.
• Develop and apply fraud tradeoff, loss avoidance, and performance measurement frameworks that quantify the impact of fraud controls across fraud loss reduction, customer experience, operational efficiency, and financial outcomes.
• Engineer, maintain, and enhance methodologies for measuring fraud benefit, losses avoided, operational costs, customer friction, false positives, and overall business impact using transparent, audit-ready approaches.
• Conduct advanced and ad hoc analytics, root-cause investigations, and performance assessments to evaluate fraud controls, identify emerging threats, uncover inefficiencies, and support optimization or decommissioning decisions.
• Monitor fraud trends, alert behavior, decision outcomes, and operational performance to identify emerging risks, changing fraud patterns, anomalies, and degradation in control effectiveness.
• Quantify expected benefits, costs, risks, operational impacts, and tradeoffs associated with fraud initiatives, tools, models, and strategic enhancements to support investment prioritization and business case development.
• Partner with Fraud Strategy, Fraud Mitigation Solutions (FMS), Risk, Operations, Digital, Technology, and AI/ML teams to align priorities, evaluate performance, validate findings, and drive measurable fraud and business outcomes.
• Support predictive fraud, AI, and analytics initiatives through performance assessment, value measurement, operational impact analysis, and ongoing benefit tracking.
• Develop and maintain performance metrics, dashboards, reporting frameworks, and executive-level insights that provide transparent visibility into fraud outcomes, decisioning effectiveness, operational efficiency, and business impact.
• Translate complex analytical findings into clear, actionable, and executive-ready recommendations that inform strategy, investment decisions, operational improvements, and continuous enhancement efforts.
• Ensure analytical rigor, data integrity, and methodological consistency by validating assumptions, strengthening measurement frameworks, and delivering decision-ready insights that can be confidently used by leadership and governance forums.

Skills

SAS

SQL

Python

Data visualization

Education

Bachelor’s degree or equivalent work experience

Tools

SAS

SQL

Python

Job description

U.S. Bank is seeking a Fraud Strategy Data Analyst to deliver enterprise-level analytics across deposits, digital, payments, and account lifecycle. You will translate complex data into decision-ready insights to optimize fraud controls and business outcomes.

The role partners with Fraud Strategy, Risk, Operations, Digital, Technology, and AI/ML teams, applying rigorous measurement frameworks while driving scalable analytics and executive-level reporting.