Fraud Strategic Data Analyst
About this role
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, enabling the communities we support to grow and succeed in the right ways, all more confidently and more often—that’s what we call the courage to thrive. 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. Try new things, learn new skills and discover what you excel at—all from Day One.
As a wholly owned subsidiary of U.S. Bank, Elavon is committed to building the platforms and ecosystems that help over 1.5 million customers around the world to achieve their financial goals—no matter what they need. From transaction processing to customer service, to driving innovation and launching new products, we’re building a range of tailored payment solutions powered by the latest technology. As part of our team, you can explore what motivates and energizes your career goals: partnering with our customers, our communities, and each other.
We actively uphold transparent and fair hiring practices that support individual opportunity, inclusive culture, and career mobility across all levels of our organisation.
We offer meaningful opportunities for growth, a culture of inclusion, and a strong commitment to transparency and integrity in everything we do.
Job Description
The Fraud Strategic Data Analyst develops data‑driven insights and strategies that strengthen fraud prevention, detection, and operational performance across deposits, payments, digital, authentication, and the end‑to‑end account lifecycle. This role combines advanced analytics, strategic problem‑solving, and cross‑functional collaboration to identify emerging fraud risks, uncover root causes, and support proactive loss mitigation.
The analyst works with a broad range of 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.
Responsibilities
- Analyze complex, multi‑channel fraud trends and performance data to identify emerging risks, root causes, and opportunities for proactive loss mitigation across the account lifecycle.
- Develop data‑driven insights and strategic recommendations that strengthen fraud prevention and detection while balancing risk, customer experience, and operational efficiency.
- Collaborate with a broad range of internal stakeholders and external partners to evaluate new and existing tools, data sources, and capabilities that enhance fraud detection and decisioning.
- Partner with the AI Center of Excellence (AI CoE) and Technology teams to evaluate, prioritize, and assess AI‑enabled fraud use cases, ensuring alignment with fraud strategy, governance standards, and measurable business outcomes.
- Translate complex analytical findings into clear, executive‑ready insights that inform enterprise fraud strategy, prioritization, and decision‑making.
- Evaluate the effectiveness of fraud controls and initiatives using key metrics, scenario analysis, and model‑adjacent analytics; identify control gaps and recommend targeted enhancements.
- Drive value‑led prioritization through cost‑benefit analysis, focusing resources on initiatives that deliver the greatest fraud risk reduction and business value while adhering to regulatory and internal control requirements.
- Additional Expectations
- Utilize approved AI tools, analytics platforms, and digital solutions to improve efficiency, accuracy, and productivity, applying sound judgment to validate outputs and ensure responsible, ethical, and compliant use.
- Maintain a strong commitment to regulatory compliance, internal controls, and risk management standards by adhering to applicable laws, policies, and procedures.
- Basic Qualifications
- Bachelor's or Masters’ degree, or equivalent work experience
- Seven to ten years of experience in risk management activities
- Preferred Skills/Experience
- Bachelor’s degree in Business, Finance, Computer Science, Business Analytics, Statistics, or another quantitative field
- SAS, SQL, R or Python experience
- Extensive data analytics experience preferably in the financial services industry
- Knowledge of financial services products, systems, and data preferably within the fraud domain
- Proficient computer skills, especially Microsoft Office applications and data analysis software
- Excellent presentation, interpersonal, written, and verbal communication skills
- Exceptional problem solving, critical thinking, and troubleshooting skills
- Ability to prioritize and manage multiple tasks, while establishing responsible deadlines
- Flexibility in day-to-day work and tolerance for ambiguity
- Positive ‘can-do’ attitude and a strong desire to continue to learn and ask questions
- The ability to work well in a team environment
- Ability to build relationships cross-functionally and over the phone
- Ability to work with and influence at all levels of the organization, including with senior leadership
- Deep understanding of fraud schemes, digital identity, authentication, and operational fraud processes
- Ability to translate analytical findings into clear business recommendations for senior leadership
- Experience supporting AI/ML‑driven fraud initiatives preferred
- This role requires working from a U.S. Bank location three (3) or more days per week.