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VP Model Risk Management - Securitized Products

Selby JenningsManhattan, NY🇺🇸United StatesPosted Oct 14, 2026

Why This Role Stands Out

This VP role offers a high-impact opportunity to lead model validation for securitized products at a renowned global investment bank, fostering significant career growth and skill development in a hybrid environment. You'll thrive here if you possess strong quantitative expertise in mortgage modeling and a desire to influence crucial risk oversight decisions. Apply today to join a dynamic team and make your mark in this critical function.

Quick Overview

Seniority
Leader
Employment type
Full Time
Work mode
Hybrid
Location
Manhattan, NY, United States
Posted
5 days ago

Job Description

A leading global investment bank is looking to hire a VP-level Model Risk professional to its growing model risk management team. This individual will focus on the independent validation and oversight of models supporting securitized products businesses, working closely with quantitative teams, risk management, and senior stakeholders.

This is a highly visible opportunity for someone with strong quantitative and mortgage modeling experience who wants to have a direct impact on model governance, risk oversight, and decision-making across a complex trading environment.

The ideal candidate will have 3+ years in model risk or related function, analyzing or validating models supporting the securitized products business.

Responsibilities:

  • Independently validate agency securitized products models, assessing methodology, assumptions, performance, and model limitations.
  • Analyze and quantify model risk, including sensitivity testing, calibration reviews, and ongoing performance monitoring.
  • Present validation findings and risk assessments to senior management, governance committees, and key business stakeholders.

Qualifications:

  • 3+ years of experience in Model Risk, Model Validation or a Quantitative role within a financial institution.
  • Strong knowledge of mortgage-backed securities, prepayment models, credit models, and the mortgage market.
  • Advanced quantitative skills with experience using Python, R, or SQL.

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