Laz Partners
Quantitative Analyst (Structured Products/ABS)
Job Location
City of London, United Kingdom
Job 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).
Location: City of London, London, GB
Posted Date: 7/13/2025
Location: City of London, London, GB
Posted Date: 7/13/2025
Contact Information
Contact | Human Resources Laz Partners |
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