VP, Portfolio Management, Quantitative Strategies Group
$200,000.00 - $250,000.00
ApplyVP, Portfolio Management, Quantitative Strategies Group
Posted 17 days ago
SENIORITY
Manager
SALARY
$200,000.00 - $250,000.00
About the role
- Credit Evaluation
- Develop and maintain analytical and statistical frameworks to evaluate collateral pools, form views on key pricing assumptions (e.g., prepayment speeds, default/loss curves). Maintain and update assumption sets based on realized performance
- Work hands-on with large loan-level datasets using Python and SQL to build analytical frameworks that evaluate collateral performance, identify risk concentrations, and inform assumption-setting across the portfolio
- Build and maintain detailed cash flow models to project expected returns, losses, and structural outcomes under base, upside, and stress scenarios
- Evaluate deal structures, waterfall mechanics, triggers, credit enhancement levels, and subordination to assess current and projected credit risk
- Valuation Allowance
- Serve as the team's primary liaison to Valuation/Risk/Accounting teams during the quarterly valuation allowance process
- Work with valuation teams to ensure appropriate quarterly reserving, incorporating the latest asset performance into existing structures
- Ensure that latest collateral performance data, updated cash flow projections, and revised assumptions are accurately reflected in valuation models and reserve estimates
- Partner with other functions within CSG and across the bank to ensure consistency in assumptions, methodologies, and market intelligence used across the group
- Investment Reporting
- Work closely with CSG teams to provide quantitative and analytical insights across existing investment positions and structured credit transactions
- Partner with technology and data teams to automate reporting pipelines and workflows, reducing manual processes and improving turnaround times
- Identify positions where realized performance is meaningfully diverging from underwriting and escalate with actionable context
- Bachelor's degree or higher in finance, economics, math, computer science or any related quantitative/analytical field 5+ years of direct experience in Structured Finance (ABS/MBS), Securitizations, or Private Credit markets is required.
- Prior experience at an Originator, Asset Manager, Investment Bank, or Rating Agency preferred
- Proficiency in advanced excel & programming is required.
- Hands-on experience in Python & SQL is critical for success in this role
- Deep expertise in building and maintaining structured credit cash flow models - waterfalls, triggers, tranche structures, and collateral analysis
- Ability to build and automate analytical workflows, data processing pipelines, model runs, and reporting tools using Python
- Foundational understanding of statistical methods (logistic/linear regression, classification, machine learning) to enhance collateral analysis and inform forward-looking risk assessments
- Excellent communication and presentation skills - ability to distill complex analytics into clear, persuasive narratives for both internal stakeholders and external counterparties
- Builder's mentality - someone who doesn't just use existing tools but actively seeks to improve how the team works by introducing new technologies, frameworks, and AI-driven efficiencies
- Ability to thrive in a fast-paced, deal-driven environment with competing priorities and tight turnaround times
- Detail-oriented with strong organizational skills and a proactive, ownership-driven mindset#LI-JJ1 #LI-Hybrid #LI-Onsite
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
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Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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