Quantitative Credit Risk Associate @ Hedge Fund

Coda Search│Staffing; United States; Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Coda Search│Staffing partners with a global asset manager to hire a Quantitative Credit Risk Associate in NYC. You will own, develop, and maintain the probability of default modeling framework and related loss estimation models across the credit platform. This is a build-oriented role working closely with deal and portfolio teams.

Requirements include 2+ years in quantitative credit risk, a STEM degree, and strong Python/SQL skills to communicate model outputs to investment professionals.

Formación

• 2+ years of experience in quantitative credit risk, modeling, validation, or related quantitative role.
• Strong applied statistical modeling and PD modeling experience.
• Comfort with Python and SQL.
• Understanding credit fundamentals and financial statements.

Responsabilidades

• Build, calibrate, and maintain PD models for private middle-market borrowers.
• Develop LGD and EAD models reflecting collateral and structures.
• Extend framework across asset classes (pool-level and cash flow modeling).
• Map internal risk ratings to external scales and study defaults.
• Back-test model output against defaults, downgrades, and recoveries.

Conocimientos

Quantitative risk

Credit modeling

Model validation

Communication of outputs

Educación

Bachelor's or Master's in STEM

Herramientas

Python

SQL

Descripción del empleo

Coda Search is partnering with a globally recognized alternative asset manager that's hiring a Quantitative Credit Risk Associate for its credit platform in NYC. The Quantitative Credit Risk Associate will own, develop, and maintain the probability of default modeling framework and related loss estimation models across the credit platform. This is a build-oriented seat and will partner closely with the deal and portfolio teams.

Responsibilities

• Build, calibrate, and maintain PD models for private middle-market borrowers
• Develop companion LGD and EAD models reflecting collateral packages, lien position, covenant structures, and observed workout recoveries.
• Extend the framework across asset classes where borrower-level modeling does not apply i.e pool-level and cash flow modeling for asset-based and structured exposures.
• Map internal risk ratings to agency-equivalent scales and external default studies.
• Back-test model output against realized defaults, downgrades, and recoveries

Qualifications

• 2+ years of experience in quantitative credit risk, credit modeling, model validation, or a closely related quantitative role at an asset manager, bank, rating agency, insurer, or specialty finance firm.
• Bachelor's or Master's degree in a quantitative discipline (STEM)
• Strong applied statistical modeling and PD modelling experience required
• Proficiency in Python and SQL. Comfort working
• Working fluency in credit fundamentals: capital structures, leveraged finance mechanics, credit agreement terms, and financial statement analysis.
• Ability to communicate model output and its limitations clearly to non-quantitative investment professionals