AI Insights & Enablement Lead

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

U.S. Bank is seeking an AI Insights & Enablement Lead to join the Artificial Intelligence Center of Excellence (AI CoE), a high-impact team responsible for accelerating the adoption of artificial intelligence across the enterprise.

This role is ideal for a highly technical and hands-on AI Data Scientist who thrives at the intersection of innovation, experimentation, and implementation. The successful candidate will identify opportunities to leverage emerging AI technologies, rapidly develop and test solutions, and help scale successful capabilities into enterprise-ready products and processes.

As a senior member of the AI CoE, you will work across the full AI development lifecycle, from translating business challenges into AI use cases through model development, experimentation, deployment, and performance optimization. You will collaborate closely with product, engineering, risk, and business teams to deliver AI solutions that drive measurable business outcomes while ensuring compliance with responsible AI, security, and governance standards.

The ideal candidate combines deep expertise in machine learning, generative AI, and advanced analytics with the practical ability to build, deploy, and scale solutions in a highly regulated environment. This individual remains at the forefront of emerging AI advancements and continuously evaluates new technologies to enhance U.S. Bank's AI capabilities.

Basic Qualifications

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or another quantitative discipline, or equivalent work experience.
Eight or more years of relevant experience in data science, machine learning, artificial intelligence, advanced analytics, or related technical disciplines.

Preferred Qualifications

Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline preferred.
8+ years of experience in data science, machine learning, artificial intelligence, or advanced analytics.
Deep expertise in machine learning, deep learning, statistical modeling, and AI solution development.
Hands-on experience designing and deploying production AI and machine learning solutions.
Strong experience with generative AI technologies, including LLMs, RAG architectures, prompt engineering, model evaluation, and fine-tuning methodologies.
Experience developing AI agent solutions, orchestration frameworks, and intelligent automation capabilities.
Proficiency in Python and modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, TensorFlow, or equivalent technologies.
Experience with cloud-based AI and machine learning platforms.
Demonstrated success translating AI concepts into scalable business solutions that deliver measurable outcomes.
Experience working within highly regulated environments such as financial services, healthcare, insurance, or telecommunications.
Strong communication, stakeholder management, and executive presentation skills, with the ability to explain complex technical concepts to diverse audiences.

Key Responsibilities

AI Solution Development & Applied Data Science

Design, develop, and deploy machine learning and artificial intelligence solutions that address complex business challenges across the enterprise.
Lead the end-to-end data science lifecycle, including data exploration, feature engineering, model development, validation, deployment, monitoring, and optimization.
Build, test, and refine predictive models, machine learning algorithms, and advanced analytics solutions using large and complex datasets.
Develop scalable AI solutions that can be integrated into enterprise applications, digital experiences, and business workflows.
Collaborate with data engineering teams to establish reliable data pipelines and ensure high-quality data assets that support AI model development and deployment.
Evaluate solution effectiveness using statistical, machine learning, operational, and business outcome metrics to drive continuous improvement.

Generative AI & Intelligent Systems

Design, build, and deploy solutions leveraging Large Language Models (LLMs), foundation models, retrieval-augmented generation (RAG), and multimodal AI capabilities.
Develop and evaluate AI agents, agent orchestration workflows, tool integrations, memory architectures, and human-in-the-loop systems that improve productivity, decision-making, and customer experiences.
Apply advanced prompt engineering, model tuning, evaluation frameworks, and inference optimization techniques to improve model effectiveness and efficiency.
Establish approaches for evaluating, monitoring, and maintaining GenAI solutions in production environments.
Assess emerging generative AI and agentic AI technologies and recommend practical applications within the bank's business and regulatory environment.

AI Innovation & Experimentation

Continuously monitor emerging AI, machine learning, and data science technologies to identify opportunities for business application.
Rapidly develop prototypes and proof-of-concepts to evaluate new technologies and demonstrate business value.
Conduct structured experimentation, benchmarking, and model comparisons to validate use cases and optimize solution performance.
Translate research findings, technical advancements, and industry developments into scalable AI solutions