Quantitative Analyst II- Equipment Finance Model Development

Overview

This is a hybrid role (if located in Morristown, NJ or Atlanta, GA) with the expectation that time working will regularly take place inside and outside of a company office. Three days a week in office. Open to remote in several markets for highly qualified candidate.

The Quantitative Analyst II of Equipment Finance of Small Business Leasing Portfolio Model Development will focus on developing and implementing sophisticated credit risk models for commercial lending portfolios. This role will be working closely with senior leadership to shape the organization's risk strategy and ensure alignment with business objectives.

Responsibilities

• Lead the development, validation, and implementation of advanced credit risk models across all commercial lending products including Small Business Leasing Portfolio.
• Partner with senior leadership to translate complex risk analytics insights into actionable business strategies and policy recommendations.
• Mentor junior model development professionals, fostering a culture of innovation and continuous improvement in risk modeling approaches.
• Drive the enhancement of risk management frameworks to meet evolving regulatory requirements, including CCAR and CECL compliance.
• Lead the response to model validation findings and oversee the implementation of remediation plans across the modeling and analytics team.
• Establish and maintain relationships with regulatory bodies, external/internal auditors, Model Risk Management and key stakeholders.
• Guide the development and implementation of new risk assessment methodologies and tools to improve the organization's risk management capabilities.
• Drive strategic initiatives to modernize risk analytics infrastructure and capabilities through adoption of advanced technologies and methodologies.

• Master's degree in Statistics, Mathematics, Finance, or related quantitative field
• At least 6 years of progressive experience in credit risk model development.
• Hands on experience using Python, SAS, Tableau.
• Hands on experience in model development and model development documentation.
• Strong understanding of regulatory requirements and experience in interactions with regulatory bodies.
• Expert knowledge of statistical modeling, machine learning techniques, and risk analytics methodologies.
• Proven track record of translating complex analytical insights into business strategy.