Senior Quant, Artificial Intelligence/Machine Learning

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 and enabling the communities we support to grow and succeed.  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 at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

We’re looking for a sharp individual contributor who’s adept at advanced AI/ML algorithms and their applications in financial institutions to join our AI/ML Validation Center of Excellence in Model Risk Management.  The team plays a critical role in providing oversight to U.S. Bank’s Artificial Intelligence Models across various business areas, such as Marketing, Fraud, Credit Risk and Bank Operations.

As a Senior Quant you will develop benchmark AI/ML models, provide validation expertise and consulting services related to AI/ML model development and model review, including best practices on algorithm development and selection, performance evaluation, implementation, monitoring, model risk mitigation and remediation. In addition, you will be responsible for conducting R&D for various AI/ML methodologies and their potential applications and use cases.

Deliverables include reviewing model development documentation, independently testing of advanced AI/ML and Generative AI models, developing technical guidance documents, training curriculum and white paper, and communicating model requirements and validation outcome to stakeholders within the Bank.

Basic Qualifications

- Bachelor’s degree in a quantitative field required with at least 10 years of relevant experience

OR

- MA/MS in a quantitative field, and 6 or more years of related experience
OR
- PhD in a quantitative field, and 5 or more years of related experience

Preferred Skills/Experience

- Strong statistical modeling or computer science background and hands on model development or validation skills

- Considerable knowledge of various machine learning algorithms and their applications, including Random Forest, GBM, XGBoost, deep learning, NLP, computer vision, and LLM.

- Experience with building complex deep learning architectures such as MLPs, RNNs,  CNNs and Generative AI frameworks such as RAG and Agentic AI.

- Strong programming skills using Python packages such as Numpy, Pandas, and scikit-learn.

- Hands on experience with deep learning or LLM software frameworks such as PyTorch, Tensorflow/Keras, MXNet, LangChain and Llamaindex are strongly preferred

- Research experience and publications on AI or Gen AI are preferred

- Experience in financial industry is preferred but not required

-  Advanced understanding of Model Risk Management and OCC SR 11-7 is a plus

- Demonstrated independence, teamwork and leadership skills
- Strong project management skills
- Excellent written and verbal communication skills

NOTE:  This role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.

If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants.

Benefits: 

Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following (some may vary based on role, location or hours):

• Healthcare (medical, dental, vision)

• Basic term and optional term life insurance

• Short-term and long-term disability

• Pregnancy disability and parental leave

• 401(k) and employer-funded retirement plan

• Paid vacation (from two to five weeks depending on salary grade and tenure)

• Up to