Jobs · Finance

Senior Associate - Portfolio Credit Risk Modeling

Ladders · United States · 4 wk ago
RemoteRemoteFinance$149k–$262k/yrFull-time
For our client, we are seeking a Senior Associate - Portfolio Credit Risk Modeling to join the team of a leader in the Finance & Insurance space. This role will focus on developing and refining portfolio-level credit risk models that support long-term investment decision-making and risk oversight. You will work closely with analysts and stakeholders to research default behavior, validate model assumptions, and communicate findings clearly to senior leaders. The position is well suited for a quantitative professional who can translate complex credit dynamics into practical insights for corporate bonds and commercial mortgage exposures. Location: Remote - US based candidates only, no visa sponsorship available Compensation: $149,000 – $262,000 annually Responsibilities Develop a multi-year stochastic credit risk model for corporate bonds and commercial mortgage loans Research credit default history and establish model assumptions Design and execute model validation processes Create analytical frameworks to clarify modeling results Guide junior analysts to enhance the credit risk modeling function Qualifications 5+ years of experience in quantitative risk modeling Proven modeling and programming skills in Python, MATLAB, or similar Strong understanding of credit default behavior and risk characteristics Deep insight into credit risk cycles and rating migration dynamics Effective communication skills for articulating complex concepts to executives Preferred designations: CFA, FRM, or actuarial credentials Benefits Medical, dental, and vision insurance Short- and long-term disability coverage Paid time off with a minimum of 18 days annually 401(k) with company match and pension plan Business casual attire and additional paid time off for Unity Day and Lifetime Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.

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