Quantitative Modelling Analyst

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

About the CRA Team
We are a highly dynamic and talented team which delivers on our mission through four pillars: Customer, Process, Talent, and Data.  

Vision | We create the future of credit risk management through data, analytics, and risk process innovation for our customers.

Mission | We deliver data-driven information solutions to protect our stakeholders and inform the most significant financial decisions in the bank. 

Values | We prioritize collaboration, integrity, simplicity, and continuous learning.

About the Role
In this role, you will develop, document, and execute processes to monitor the performance and stability of predictive models used in Credit Risk Management. You’ll also collaborate with model developers to support new model development initiatives.

The ideal candidate has strong programming and analytical skills, enjoys solving technical problems, and thrives in a collaborative environment.

Key Activities

• Develop and optimize code and processes for model performance monitoring and reporting.

• Analyze model metrics (e.g., accuracy, stability), identify issues, and recommend improvements.

• Conduct tests, interpret results, and present findings through reports and dashboards.

• Collaborate with development and implementation teams to align data and execution logic.

• Automate data capture, testing, documentation, and visualization workflows.

• Create documentation and playbooks to ensure process consistency and knowledge sharing.

• Support new model development projects in partnership with the model development team.

• Explore ML/AI techniques to enhance process efficiency.

Basic Qualifications

• 3 or more years of experience in a data analytics, software development, or related roles.

• Bachelor’s Degree or higher in a quantitative/technical field such as statistics, mathematics, computer science, data science, or engineering.

• Programming experience in Python (preferred) or similar statistical software (e.g. R, SAS)

• Proficiency in developing and optimizing SQL queries.

• Strong analytical, organizational, problem-solving, and project management skills.

• Effective interpersonal, verbal, and written communication skills.

Preferred Skills

• Experience in financial services, banking, and/or credit risk.

• Data visualization dashboard technologies such as Power BI.

• Experience with cloud-based tools and infrastructure (Azure or AWS).

• Familiarity with automation using scripting tools (e.g. Bash) and low-code platforms (Microsoft Power Automate / Power Apps).

• Experience with quantitative model development and/or validation.

• Exposure to machine learning concepts and their application in financial services.

• Understanding of version control systems like Git.

Location

This role requires working from a U.S. Bank location three (3) or more days per week. 

Accessibility

We are committed to providing an inclusive and accessible recruitment experience. If you need adjustments at any stage of the application or hiring process, please contact your recruiter for guidance and support.

Total Rewards

U.S. Bank is committed to fair, equitable, and transparent compensation practices in line with local regulatory and legal requirements. Our total rewards approach is designed to attract, retain, and support top talent while ensuring equal pay for work of equal value.

We offer a market-competitive compensation package that includes:

• Clearly defined salary ranges aligned with industry benchmarks and internal equity standards.

• Performance-based incentives for eligible employees (as defined by relevant plan rules), awarded through transparent, objective criteria that recognize both individual and company performance.

• Inclusive equitable benefits that are accessible to all employees and focused around our 3 main pillars of financial wellbeing, health & wellness).

• Continuous development opportunities including training, education support, and career progression pathways based on inclusive and transparent criteria.

• Employee recognition programs that celebrate achievements and milestones for all.

We regularly review our compensation and benefits to ensure they remain competitive, inclusive, and responsive to employee needs and market trends. Further details of the compensation package will be provided upon application.

We encourage candidates to explore the full value of our offer, including monetary and non-monetary benefits, at Employee benefits and development | U.S. Bank | Elavon.

Closing Date

Posting may be closed earlier due to high volume of applicants.

We aim to provide timely updates throughout the process and encourage early applications to ensure consideration.