At a Glance
- Tasks: Own the end-to-end development of advanced pricing and risk management models.
- Company: Join a leading firm specializing in quantitative finance and fixed income modeling.
- Benefits: Enjoy autonomy, competitive salary, and opportunities for professional growth.
- Why this job: Shape your research direction while working on cutting-edge financial models.
- Qualifications: Advanced degree in a quantitative field and strong programming skills required.
- Other info: Ideal for self-starters who thrive in a fast-paced, independent environment.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Senior Quantitative Developer/Engineer
This role will suit an autonomous and technically adept quant with deep expertise in fixed income modeling, who thrives on owning the end-to-end development process—from data sourcing and cleaning, to model design, back-testing, and performance optimization. The successful candidate will seamlessly combine rigorous mathematical modeling with advanced computational techniques, all while maintaining top-tier coding standards, documentation, and compliance readiness.
Role Overview:
As a Senior Quantitative Researcher, you will play a key role in the end-to-end development and refinement of advanced pricing, risk management, and trading models—particularly within the fixed income and rates space. The ideal candidate will operate autonomously, taking full ownership of the research pipeline, from initial hypothesis formation and data sourcing to model coding, testing, and implementation. Without the traditional support of business analysts, you will have the freedom and responsibility to shape the direction of your research and ensure the robustness, accuracy, and scalability of your models.
Key Skills & Capabilities:
Fixed Income & Derivatives Modeling:
# Proficiency in building and calibrating interest rate curves and employing advanced stochastic volatility frameworks for pricing and risk management of interest rate options.
Mathematical & Quantitative Techniques:
# Strong grasp of numerical methods, optimization, and Monte Carlo simulation, enabling the construction of arbitrage-free curves, parameter stability, and model convergence under various market conditions.
Programming & Automation:
# Expertise in Python, C++, or similar languages, with a focus on data ingestion, ETL automation, high-performance computing, parallelization, and memory management to ensure timely and efficient computations.
Statistical Validation & Back-Testing:
# Ability to design and maintain robust back-testing frameworks, apply rigorous statistical analyses, hypothesis testing, and performance metrics to validate and refine trading signals and model assumptions.
Data Handling & Integration:
# Competence in acquiring, cleaning, and integrating complex datasets from multiple sources without external support, ensuring data integrity, reproducibility, and scalability.
Documentation & Model Governance:
# Commitment to disciplined coding practices, comprehensive documentation, version control, and auditability to meet internal risk standards, comply with regulatory requirements, and maintain high-quality model governance.
Key Responsibilities:
Model Development & Enhancement:
Independently conceive, design, and optimize quantitative models for interest rate derivatives, government bonds, and other related fixed income products.
Data Pipeline Management:
Identify, gather, clean, and prepare data sources—both historical and real-time—integrating them seamlessly into the research framework without dedicated business analyst support.
Back-Testing & Validation:
Implement rigorous performance tests, run simulations, stress-test model assumptions, and continuously refine approaches based on empirical results and changing market conditions.
End-to-End Ownership:
Oversee all stages of research execution, from initial idea generation to final coding, deployment, and documentation, ensuring that models adhere to high standards of governance, auditability, and reproducibility.
Strategic Collaboration:
Communicate complex modeling concepts, performance metrics, and insights effectively to portfolio managers, traders, and risk managers, ensuring models align with broader portfolio objectives and risk parameters.
Ideal Candidate Profile:
Educational Background:
An advanced degree (PhD or Master’s) in a quantitative field—such as Mathematics, Physics, Engineering, or Computer Science—from a top-tier institution.
Domain Expertise:
Proven experience with fixed income instruments, yield curve construction, and interest rate volatility modeling.
Technical Proficiency:
~ Strong programming skills in Python, C++, or similar languages. Familiarity with quantitative libraries, version control, and production-level code deployment is essential.
Independent Execution:
~ Demonstrated ability to handle every aspect of the research cycle without delegated support. Skilled at data wrangling, model calibration, and the proactive troubleshooting of technical issues.
Analytical Mindset & Curiosity:
~ Highly analytical, detail-oriented, and intellectually curious, with a genuine passion for exploring innovative quantitative methods and adapting models to evolving market conditions.
Clear Communication:
~ Ability to distill complex quantitative findings into actionable insights and convey them effectively to both technical and non-technical stakeholders.
IT Developer & Support employer: Intelix.AI
Contact Detail:
Intelix.AI Recruiting Team
We think you need these skills to ace IT Developer & Support
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Quantitative Developer/Engineer position. Familiarize yourself with fixed income modeling and the specific skills mentioned in the job description.
Tailor Your CV: Customize your CV to highlight relevant experience in quantitative modeling, programming languages like Python or C++, and any previous work with fixed income instruments. Use specific examples that demonstrate your expertise and achievements in these areas.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your passion for quantitative research and your ability to work autonomously. Mention how your background aligns with the key responsibilities and skills outlined in the job description.
Highlight Technical Skills: In your application, emphasize your technical proficiency in programming, data handling, and statistical validation. Provide examples of projects where you successfully implemented complex models or automated processes, showcasing your problem-solving abilities.
How to prepare for a job interview at Intelix.AI
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with fixed income modeling and quantitative techniques in detail. Highlight specific projects where you built or optimized models, and be ready to explain the methodologies you used.
✨Demonstrate Independent Problem-Solving
Since the role requires autonomy, share examples of how you've independently managed the research pipeline. Discuss challenges you faced and how you overcame them without relying on external support.
✨Communicate Complex Concepts Clearly
Practice explaining your quantitative findings in a way that is accessible to both technical and non-technical audiences. This will be crucial when collaborating with portfolio managers and traders.
✨Prepare for Technical Questions
Expect questions related to programming in Python or C++, as well as statistical validation and back-testing frameworks. Brush up on your coding skills and be ready to solve problems on the spot.