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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: Tackle real-world financial challenges while collaborating with experts in a dynamic environment.
- Qualifications: Degree in a quantitative field; coding experience in Python; understanding of structured products required.
- Other info: Ideal for those passionate about finance and data analytics, with opportunities for cross-functional collaboration.
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 products and asset-backed financing. This will not only help you understand the market dynamics but also allow you to engage in informed discussions during interviews, showcasing your knowledge and enthusiasm for 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, as this practical experience can be a great talking point in interviews.
✨Tip Number 3
Network with professionals in the finance and quantitative analysis sectors. Attend industry conferences, webinars, or local meetups to connect with potential colleagues or mentors who can provide insights into the role and possibly refer you internally.
✨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 quantitative insights have led to successful outcomes, as this will demonstrate your ability to add value to the team.
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 modeling, and programming skills, particularly in Python. Emphasise any work you've done with structured products or asset-backed financing.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in mathematics, statistics, or computer science aligns with the job requirements, and mention specific projects where you've applied quantitative techniques.
Showcase Technical Skills: Clearly outline your technical skills in your application. Mention your experience with cloud platforms like AWS, data analytics, and any familiarity with tools such as Intex or structured product analytics platforms. Provide examples of how you've used these skills in past roles.
Prepare for Technical Questions: Anticipate technical questions related to quantitative analysis and structured products during the interview process. Brush up on statistical methods and be ready to discuss your approach to solving complex financial problems.
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, especially regarding SRT transactions and ABS structures.
✨Communicate Clearly
Practice explaining complex quantitative concepts in simple terms. Since you'll need to engage with non-technical stakeholders, being able to translate your technical knowledge into understandable insights is crucial.
✨Demonstrate Collaboration Skills
Prepare examples of how you've successfully collaborated with cross-functional teams in the past. This could include working with risk, trading, or technology teams, as showcasing your ability to work well with others will be key for this role.
