Leader in credit risk model development within U.S. Bank's Model Development & Decision Science team. Overseeing compliance with regulatory requirements and effective risk management practices.
Responsibilities
Oversee the development of expected loss forecasting models for the Commercial & Industrial portfolio in compliance with CECL, CCAR and other regulatory requirements
Interface with staff in credit portfolio risk management, corporate finance, external reporting, as well as model validation and audit services
Communicate statistical model functions and predictions to stakeholders to demonstrate effective risk management and compliance
Foster integrations of credit risk modeling into business as usual (BAU) activities
Develop and document model methodology and selection evidence for validation and third-party review
Present final development code for validation and implementation using coding languages (Python, R, SAS, SQL)
Systematically track and report on the ongoing performance and stability of models
Documentation and presentation of portfolios analysis supporting modeled outputs, respective overlays for emerging risks and reasonableness analysis
Oversee offshore resources to supplement support the U.S.-based team
Requirements
Bachelor’s degree (MA/MS/PhD strongly preferred) and eight or more years of relevant experience
Four or more years of experience leading a quantitative modeling team
Master's Degree or PhD in a quantitative field such as computer science, data science, mathematics, or statistics (preferred)
10 or more years of experience in a leadership role in model development/implementation, software engineering, or related area (preferred)
Strong familiarity with credit risk modeling and industry-standard approaches (e.g. PD, LGD, EAD)
Deep understanding of banking, financial metrics, and credit risk management
Knowledge of banking regulation and requirements for stress testing and credit reserves
Demonstrated success attracting talent, building, and leading teams of model developers or analysts in similarly technical fields
Excellent executive presence and verbal and written communication skills
Ability to build strong relationships with a wide range of individuals from risk, finance, model validation, technology, and regulators
Strong analytical and problem solving skills, coupled with thoroughness and attention to detail
Ability to prioritize work, meet deadlines, work under pressure and independently while balancing multiple priorities in a dynamic and complex environment
Strong analytical, organizational, problem-solving, and project-management skills
Experience working with large datasets and building or validating advanced statistical models (including regression and economic factor models)
Extensive experience in building credit models for commercial exposures
Experience interpreting and applying Basel A-IRB, CCAR/DFAST, CECL regulatory rules and experience working with financial institution regulatory agencies
Experience working with internal model validation and model risk management
Programming experience in Python, SAS (Base, STAT, and/or Enterprise Guide)
Experience with MS Word, Excel, and PowerPoint
Automation using Bash/shell scripting and orchestration tools like Apache Airflow
Relational databases, SQL query optimization
Code management and version control using Git
Cloud-based solution deployment (AWS or Azure) and containerization/orchestration tools (e.g. Docker, Kubernetes)
Al/ML and GenAI approaches
Microsoft Power Automate/ Power Apps
PowerBI or other visualization dashboards
Benefits
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 11 paid holiday opportunities
Adoption assistance
Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law
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