Quant Investment Strategist – Portfolio Management Associate

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.

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.

• Tools:

Familiarity with credit analytical tools (e.g., Intex, Bloomberg, or Moody’s Analytics) is a plus.