Credit Risk Administration – Head of Transformation, Data Strategy and Information Insights; TDSI

Overview

Credit Risk Administration – Head of Transformation, Data Strategy and Information Insights (TDSI) at U.S. Bank. We are seeking a visionary and dynamic leader to head the Credit Transformation, Data Strategy, and Information Insights (TDSI) team within the Credit Risk Administration (CRA) function. This executive will drive modernization and transformation of credit data and reporting in alignment with the Enterprise Data Strategy, championing advanced technologies, cloud solutions, and data analytics to elevate risk management capabilities.

We are a highly dynamic team delivering on our mission through four pillars:
Customer, Process, Talent, and Data. Our vision is to create the future of credit risk management through data, analytics, and risk process innovation for our customers. Our mission is to deliver data-driven information solutions to protect stakeholders and inform significant financial decisions in the bank. Values include collaboration, integrity, simplicity, and continuous learning.

The ideal candidate will possess deep expertise in credit risk, data strategy/governance, and analytics, with a proven track record of leading multidisciplinary teams through complex transformation initiatives. This leader will shape and execute the strategic vision for credit data and reporting, ensure operational excellence, regulatory compliance, and alignment with enterprise data strategies including executing the global delivery strategy.

Responsibilities include balancing hands-on management of daily operations with strategic modernization, driving automation and process innovation to deliver efficiencies across the Credit Risk Management platform. The role represents Credit Risk on multiple strategy committees and involves collaboration with business stakeholders, Risk Managers, Model Owners, Technology teams, Source System owners, Business Line partners, Data Strategy and Data Domain owners, and Reporting functions.

• Establish a credit risk data framework with definitions, data quality scorecards, and governance in centralized cloud solutions.
• Align historical modeling, forecasted and unstructured data to strategy and cloud solutions for broader insights/usage.
• Develop and implement data and reporting solutions for wholesale and retail portfolios; promote dashboards, automated workflows, and delivery mechanisms.
• Represent credit risk reporting and data strategy in enterprise-wide initiatives and critical projects.
• Collaborate with Subject-Matter Experts to gather requirements, design data models, and implement validation and reconciliation controls.
• Support system conversions and cloud migration efforts with minimal disruption.
• Promote a culture of continuous improvement, collaboration, and learning.
• Build partnerships across business lines, technology, and data domain owners to deliver scalable, cloud-enabled solutions.
• Leverage AI tools and platforms to enhance productivity and reporting workflows.
• Drive integration of global delivery efforts.

• Deep understanding of credit data across Commercial and Retail portfolios.
• Experience in data governance and analytics within financial services (e.g., Basel III, CCAR, CECL, regulatory submissions).
• Data modeling, analytics, and integrating historical, forecasted, and unstructured data.
• Dashboard creation, automated workflows, and scalable delivery for wholesale and retail portfolios.
• Ability to represent credit risk in enterprise projects and committees.
• Experience supporting system conversions and cloud migration.
• Analytical skills for issue remediation.

• Cloud data architecture and tooling (e.g., Spark, Airflow, AWS, Azure, Snowflake, Databricks).
• Familiarity with AI tools (e.g., Microsoft Copilot, Power Platform).
• Cloud platforms (Azure, AWS, GCP) and cloud-native data services.
• SQL, Python or similar languages;
  Power Platform (Power Automate, Power Apps, Power
  
  BI).
• Big data technologies (Spark, Airflow, Hadoop, Hive).

• Promote continuous improvement, collaboration, and learning.
• Strong stakeholder engagement and cross-functional collaboration.
• Experie…