Credit Risk Analytics, Vice President

Mizuho•New York City, NY

16h•Hybrid

About The Position

Mizuho Americas Enterprise Risk Management is seeking a Vice President (VP) to develop, remediate, and maintain quantitative credit risk models and analytics within the Risk Analytics team in New York City. Risk Analytics owns the end-to-end model lifecycle, from methodology design and implementation to ongoing performance monitoring. The role covers wholesale credit loss, ratings, securitization, counterparty, and stress testing models. The VP will ensure strong governance and regulatory alignment, apply AI-enabled tools to improve efficiency, and partner across Risk, Finance, Technology, and Model Risk Management through development, validation, and implementation.

Requirements

5–7 years of experience in quantitative modeling for credit, stress testing, market risk, or liquidity risk.
Master’s degree in a quantitative discipline (e.g., mathematics, statistics, finance, or programming).
Proficient programming skills: Python, MATLAB, Microsoft Excel VBA, Bloomberg, and leading AI tools.
Expertise in statistical methods, including regression analysis, time series forecasting (e.g., Bayesian inference and tools for regime switching), and machine learning.
Demonstrable experience with stakeholder interactions, project management, and organizational skills.
Strong writing and presentation skills to translate technical concepts for non-technical stakeholders.

Responsibilities

Partner with business stakeholders to design, develop, and test credit risk models (such as expected-loss, ratings, securitization, counterparty, PD, LGD, and EAD models) for wholesale and commercial portfolios, supporting stress testing and regulatorily compliant risk frameworks.
Oversee ongoing support, performance monitoring, and enhancement of the existing suite of credit models; develop methodologies and algorithms for new models and risk analytics initiatives.
Apply AI and analytics tools to improve the function’s efficiency (e.g., to perform and document ongoing model monitoring tests, including sensitivity analyses).
Lead the implementation of model changes and remediation plans using advanced statistical techniques.
Work with stakeholders across business and functional teams, including Model Risk Management, during model development, validation, and implementation to ensure rigorous testing, well-documented methodologies, and compliance with internal and regulatory requirements.
Support internal and external remediation, regulatory submissions, and discussions with regulators and control functions as a subject matter expert; address feedback from regulators and Internal Audit.