Quantitative Risk Modeling Lead

Huntington Bancshares Inc•Columbus, OH

56d•$93,000 - $189,000•Onsite

About The Position

Quantitative Risk Modeling Lead Summary: The Quantitative Risk Modeling Lead is responsible for overseeing the development, implementation, and monitoring of advanced quantitative models for consumer and commercial credit, PPNR, loan origination, and portfolio management. This role requires a deep understanding of statistical modeling, machine learning, and risk management frameworks, along with strong leadership and project management skills. This role is designed for an experienced professional who can lead the development and implementation of advanced quantitative models, oversee and guide analysts, review work performed by analysts, and manage multiple projects effectively.

Requirements

Master's degree in a quantitative field (mathematics, statistics, economics, engineering, finance, physics).
5+ years of experience in statistical modeling using SQL, SAS, R, and Python
5+ years of experience in machine learning and data mining

Nice To Haves

PhD in a quantitative field.
Extensive knowledge of CCAR/DFAST and CECL concepts and frameworks.
Proven ability to lead complex projects and supervise junior modeling analysts.
Deep understanding of loss forecasting, loan origination, and portfolio management modeling concepts (PD, LGD, EAD).
Exceptional analytical skills, comprehensive understanding of risk concepts and frameworks, strong communication skills, proficiency in MS Office products, and a solid grasp of economic concepts.
Demonstrated passion and drive for operational excellence and quality delivery.

Responsibilities

Model Development: Lead the creation and enhancement of complex quantitative models for credit risk, PPNR, loan origination, and portfolio management.
Data Analysis: Oversee the analysis of credit portfolio performance data to identify trends, risks, and opportunities.
Model Monitoring: Ensure ongoing monitoring and validation of existing models, including reporting and analysis of results.
Advanced Model Building: Compile and process historical data, perform sophisticated data analysis using AI/ML tools, build and refine models using regression analysis and ML tools, and oversee implementation and production.
Research: Drive research initiatives to explore new modeling methodologies and techniques, staying abreast of industry advancements.
Collaboration: Coordinate with various teams to support governance, audit/compliance, and validation projects related to developed models.
Leadership: Mentor and supervise more junior modeling analysts, providing guidance and support to ensure high-quality model development and implementation through the performance of technical reviews.
Project Management: Manage multiple projects simultaneously, ensuring timely delivery and adherence to strict deadlines.
Performance Analysis: Conduct in-depth analysis of credit portfolio performance data, providing actionable insights to senior management.
Ad-Hoc Analytics: Lead ad-hoc analytics projects to address specific business needs and challenges.
Other Duties: Perform additional duties as assigned, contributing to the overall success of the risk modeling team.