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- Tasks: Join a top-tier team to develop quantitative models for structured credit and asset-backed investments.
- Company: Work with a leading global asset manager known for its innovative investment strategies.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by applying advanced techniques to solve complex financial challenges in a collaborative environment.
- Qualifications: Degree in a quantitative field; experience in Python and financial modelling is essential.
- Other info: Ideal for those passionate about finance and technology, eager to learn and innovate.
The predicted salary is between 43200 - 72000 £ per year.
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.
- 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).
Quantitative Analyst (Structured Products/ABS) employer: Laz Partners
Contact Detail:
Laz Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst (Structured Products/ABS)
✨Tip Number 1
Familiarise yourself with the latest trends in structured credit and asset-backed financing. Understanding current market dynamics will not only help you in interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Brush up on your Python skills, especially in relation to financial modelling. Consider working on personal projects or contributing to open-source projects that involve quantitative analysis to showcase your coding abilities.
✨Tip Number 3
Network with professionals in the finance and quantitative analysis sectors. Attend industry events or webinars where you can meet potential colleagues and learn more about the specific challenges they face in structured products.
✨Tip Number 4
Prepare to discuss how you've used data analytics to drive investment decisions in past roles. Be ready to share specific examples of how your insights have led to successful outcomes, as this will resonate well with hiring managers.
We think you need these skills to ace Quantitative Analyst (Structured Products/ABS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative analysis, financial modelling, and coding in Python. Emphasise any work you've done with structured products or asset-backed financing to align with the job requirements.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss specific projects or experiences that demonstrate your technical skills and understanding of structured credit and ABS. Make it personal and show how you can contribute to their team.
Showcase Technical Skills: Include a section in your application that details your technical skills, particularly in Python and cloud services like AWS. Mention any relevant tools or platforms you've used, such as Intex or structured product analytics, to strengthen your application.
Prepare for Interviews: If selected for an interview, be ready to discuss your previous projects in detail. Prepare to explain complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
How to prepare for a job interview at Laz Partners
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on coding experience, particularly in Python. Highlight specific projects where you've developed financial models or worked with large datasets, as this will demonstrate your technical proficiency and relevance to the role.
✨Understand Structured Products
Make sure you have a solid grasp of structured product mechanics and asset-backed financing. Be ready to explain how these concepts apply to real-world investment scenarios, as this knowledge is crucial for the role.
✨Communicate Clearly
Practice explaining complex quantitative concepts in simple terms. The ability to bridge the gap between technical and non-technical audiences is essential, so think of examples where you've successfully communicated your ideas.
✨Demonstrate Collaboration Skills
Prepare to discuss your experience working in cross-functional teams. Share examples of how you've partnered with investment, risk, and technology teams to integrate quantitative outputs into decision-making processes.
