Quantitative Model Analyst

At U.S. Bank were 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 oftenthats 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 atall 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 goalsno matter what they need. From transaction processing to customer service to driving innovation and launching new products were 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

We are now hiring for an exciting opportunity as Quantitative Model Analyst 3 within U.S. Bancorps Enterprise Fraud Strategy team.

The successful candidate will play a key role in U.S. Banks Enterprise Fraud Strategy team. The Quantitative Modeling Analyst position creates validates tests documents implements and/or oversees usage of complex machine learning models strategies and profile development. The algorithms may cover a variety of products or services; however all algorithms are used as part of the financial decision-making or fraud detection processes. Specific results focus on documenting the creation and/or testing of machine learning models and communicating such models to stakeholders within the Bank. Deliverables include the creation of model development and/or validation documentation such as presentations written reports model or reporting code documentation business requirements monitoring reports and related code and procedures.

Basic Qualifications

• Bachelors degree in a quantitative field and five to eight years of experience in statistical modeling OR

• Masters or PhD degree in a quantitative field and less than five years of experience in statistical modeling

Preferred Skills/Experience

• Proficiency in machine learning techniques and frameworks for fraud detection including but not limited to logistic regression decision trees random forest SVM gradient boosting and neural networks using Python or similar coding language

• Experience planning building and deploying predictive features to be used in fraud rules or model inputs based on aggregate or historical transaction analysis strongly preferred

• Experience coding in various languages (SQL R Python SAS etc.) to explore and perform analytical analysis on large disparate and complex data.

• Self-motivated individual with demonstrated thought leadership and planning for quantitative modeling and analytical projects development efforts.

• Thorough knowledge of fraud strategic planning and banking operations.

• Comprehensive knowledge of bank systems banking documents and financial products including credit cards ACH transactions wires checks and other electronic transfers.

• Advanced understanding of applicable laws regulations financial services and regulatory trends that affect assigned line of business.

• Demonstrated independence teamwork leadership and critical thinking skills.

• Strong project management skills.

• Strong understanding of model governance and risk management practices including documentation validation and regulatory compliance (e.g. SR 11-7 CCAR).

• Excellent written and verbal communication skills.

• Demonstrated project management organization skills and Agile experience

Hybrid/flexible schedule Location Expectations;

The role offers a hybrid/flexible schedule which means theres an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.

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.