Quant Investment Strategist - Portfolio Management Associate
Coda Search│Staffing, New York, NY, United States
We are seeking a highly analytical
Quant Investment Strategist / Portfolio Management Associate
to join a top performing Credit team of a $100B asset manager. In this role, you will be the primary engine behind the modeling and analytics that drive our portfolio construction and asset allocation.
Please ensure you read the below overview and requirements for this employment opportunity completely.
Working directly with the Senior Portfolio Manager (PM), you will leverage advanced quantitative techniques to build and optimize credit portfolios, with a heavy focus on
Structured Products
(CLOs, ABS, RMBS/CMBS) and
Private Credit
(Direct Lending, Specialty Finance). You will bridge the gap between complex data architecture and real-world investment execution. Key Responsibilities Portfolio Construction & Optimization Develop and maintain sophisticated models for
Asset Allocation
across various credit sub-sectors. Implement optimization frameworks (e.g., Mean-Variance, Black-Litterman, or Factor-based) tailored for illiquid and structured credit assets. Conduct "What-if" scenario analysis to determine the impact of new deal inclusions on portfolio yield, duration, and risk-weighted capital. Quantitative Modeling & Analytics Build cash flow engines and valuation models for complex
Structured Products . Develop proprietary risk models to capture non-linear risks inherent in private credit and leveraged structures. Create automated tools for performance attribution, identifying drivers of alpha within the credit book. Strategic Decision Support Partner directly with the PM to provide data-driven insights for investment committee memos. Monitor market signals and spread movements to suggest tactical rebalancing opportunities. Synthesize large datasets of loan-level data to identify structural trends in the private credit landscape. Required Advanced Degree (Masters or PhD):
Required in a STEM field (Mathematics, Physics, Financial Engineering, Computer Science, or Statistics). Experience:
3–7 years of professional experience in a quantitative research or portfolio management environment. Domain Expertise:
Demonstrated knowledge of
Credit Markets . Experience with Structured Products (CLOs) or Private Credit is highly preferred. Programming:
Expert-level proficiency in
Python
(NumPy, Pandas, Scikit-learn) or
R . Database/SQL:
Ability to manipulate and query large-scale financial datasets. Optimization:
Deep understanding of stochastic calculus, linear algebra, and optimization libraries. xywuqvp Tools:
Familiarity with credit analytical tools (e.g., Intex, Bloomberg, or Moody’s Analytics) is a plus.
Quant Investment Strategist / Portfolio Management Associate
to join a top performing Credit team of a $100B asset manager. In this role, you will be the primary engine behind the modeling and analytics that drive our portfolio construction and asset allocation.
Please ensure you read the below overview and requirements for this employment opportunity completely.
Working directly with the Senior Portfolio Manager (PM), you will leverage advanced quantitative techniques to build and optimize credit portfolios, with a heavy focus on
Structured Products
(CLOs, ABS, RMBS/CMBS) and
Private Credit
(Direct Lending, Specialty Finance). You will bridge the gap between complex data architecture and real-world investment execution. Key Responsibilities Portfolio Construction & Optimization Develop and maintain sophisticated models for
Asset Allocation
across various credit sub-sectors. Implement optimization frameworks (e.g., Mean-Variance, Black-Litterman, or Factor-based) tailored for illiquid and structured credit assets. Conduct "What-if" scenario analysis to determine the impact of new deal inclusions on portfolio yield, duration, and risk-weighted capital. Quantitative Modeling & Analytics Build cash flow engines and valuation models for complex
Structured Products . Develop proprietary risk models to capture non-linear risks inherent in private credit and leveraged structures. Create automated tools for performance attribution, identifying drivers of alpha within the credit book. Strategic Decision Support Partner directly with the PM to provide data-driven insights for investment committee memos. Monitor market signals and spread movements to suggest tactical rebalancing opportunities. Synthesize large datasets of loan-level data to identify structural trends in the private credit landscape. Required Advanced Degree (Masters or PhD):
Required in a STEM field (Mathematics, Physics, Financial Engineering, Computer Science, or Statistics). Experience:
3–7 years of professional experience in a quantitative research or portfolio management environment. Domain Expertise:
Demonstrated knowledge of
Credit Markets . Experience with Structured Products (CLOs) or Private Credit is highly preferred. Programming:
Expert-level proficiency in
Python
(NumPy, Pandas, Scikit-learn) or
R . Database/SQL:
Ability to manipulate and query large-scale financial datasets. Optimization:
Deep understanding of stochastic calculus, linear algebra, and optimization libraries. xywuqvp Tools:
Familiarity with credit analytical tools (e.g., Intex, Bloomberg, or Moody’s Analytics) is a plus.