AI/ML Quant Analyst — Model Risk & GenAI Innovator

U.S. Bank; Minneapolis (MN); On-site; USD 120,000 - 141,000; Full time

Benefits offered by this job

Healthcare

Life Insurance

Disability Insurance

Parental Leave

401(k)

Paid Vacation

Job summary

U.S. Bank is seeking a sharp Quant to join the AI/ML Validation Center of Excellence in Model Risk Management. You will develop benchmark AI/ML models, validate approaches, and document results for stakeholders.

You’ll review development documentation, test advanced AI/ML and GenAI/Agentic AI models, and contribute to training and white papers. The role requires strong quantitative education and hands-on ML experience, with emphasis on modern architectures, evaluation methods, and risk-aware

Qualifications

• Advanced AI/ML expertise with model development and validation experience.
• Strong programming in Python with common ML libraries.
• Knowledge of ML algorithms and deep learning for GenAI use cases.
• Experience in multi-agent AI, tool-augmented workflows, and evaluation.

Responsibilities

• Develop benchmark AI/ML models and conduct validation activities.
• Review model development docs and perform independent testing.
• Create technical guidance, training materials, and white papers.
• Communicate model requirements and validation outcomes to stakeholders.

Skills

AI/ML Validation

Python

ML Algorithms

GenAI

NLP

Deep Learning

Team Leadership

Education

Bachelor’s degree

MA/MS in quantitative field

PhD in quantitative field

Tools

NumPy

Pandas

scikit-learn

PyTorch

TensorFlow

LangChain

Job description

U.S. Bank is seeking a sharp Quant to join the AI/ML Validation Center of Excellence in Model Risk Management. You will develop benchmark AI/ML models, validate approaches, and document results for stakeholders.

You’ll review development documentation, test advanced AI/ML and GenAI/Agentic AI models, and contribute to training and white papers. The role requires strong quantitative education and hands-on ML experience, with emphasis on modern architectures, evaluation methods, and risk-aware