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Quantitative analyst (structured products/abs)

Slough
Laz Partners
Quantitative analyst
Posted: 6 July
Offer description

Role Overview

We have partnered with a Tier-1 global asset manager looking to hire a Quantitative Analyst to join a highly respected team, with a focus on structured credit and asset-backed financing. This role blends quantitative research, model development, and data analytics, offering the opportunity to work on complex financial instruments within a high-performing investment platform.


The ideal candidate will bring strong technical skills, hands-on coding experience, and a solid understanding of structured product mechanics. This is a unique opportunity to apply advanced quantitative techniques to real-world investment problems while working closely with portfolio managers, risk, trading, and technology.


Key Responsibilities

* Financial Engineering: Design and enhance quantitative models to evaluate structured credit and asset-backed investments, including significant risk transfer (SRT) transactions and other ABS structures, ensuring they reflect market dynamics and risk sensitivities.
* Data-Driven Insights: Analyze large, complex datasets using Python and cloud-based tools to generate actionable investment insights.
* Infrastructure Development: Maintain and optimise analytics infrastructure using cloud services (e.g., AWS) and database systems to support modeling and data workflows.
* Stakeholder Engagement: Partner with investment, risk, and technology teams to integrate quantitative outputs into portfolio construction and risk frameworks.
* Knowledge Translation: Clearly communicate technical concepts to non-technical audiences, ensuring model assumptions and outputs are well understood.
* Cross-Functional Collaboration: Contribute to cross-asset initiatives and research projects, working alongside peers from other quantitative functions across the platform.


Requirements & Qualifications

* Degree in a quantitative field such as Mathematics, Statistics, Engineering, Physics, or Computer Science (advanced degree such as a Master’s or PhD preferred).
* Proven experience developing financial models in Python and bringing code into production environments.
* Strong understanding of structured products and the underlying mechanics of asset-backed financing, with direct exposure to SRT transactions and other ABS instruments (highly preferred).
* Deep familiarity with statistical methods and applied mathematics in a financial context.
* Exposure to cloud platforms (e.g., AWS) and experience managing large datasets through modern data infrastructure.
* Ability to work through complex problems independently and collaboratively, with a solution-oriented mindset.
* Excellent communication skills, with the ability to bridge technical and investment audiences effectively.
* Experience working with Intex, loan-level data, or structured product analytics platforms (preferred).
* Familiarity with delinquency, prepayment, or recovery modeling for structured credit products (a plus).

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