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- Tasks: Validate pricing, risk, and regulatory models for trading and risk management.
- Company: Join a leading Investment Bank's Risk team focused on quantitative analysis.
- Benefits: Competitive pay based on skills; potential for remote work and flexible hours.
- Why this job: Engage in impactful work with cutting-edge tools in a fast-paced environment.
- Qualifications: Degree in a quantitative field; programming skills in C# and Python required.
- Other info: This is a 6-month rolling contract at a mid-senior level.
The predicted salary is between 43200 - 72000 £ per year.
This range is provided by Bonhill Partners. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
We’re currently supporting an Investment Bank in their search for a Model Validation Quant to join their Risk team. The successful candidate will be responsible for validating pricing, risk, and regulatory models used across various asset classes. This role involves model documentation, regulatory reporting, model testing, and calibration, with programming required for model implementation and validation.
Key Responsibilities:
- Conduct independent validation of pricing, risk, and regulatory models used in trading and risk management.
- Develop and implement model validation methodologies, ensuring compliance with regulatory requirements (e.g., Basel, SS1-23, FRTB).
- Perform rigorous testing, backtesting, stress testing, and benchmarking of models to assess accuracy and stability.
- Review and enhance model documentation to ensure transparency, completeness, and regulatory compliance.
- Work closely with front office quants, risk managers, and technology teams to assess model performance and resolve issues.
- Provide regulatory reporting support, ensuring compliance with internal and external regulatory standards.
- Implement and test model validation tools using C# and Python.
- Perform model recalibration and ensure continuous monitoring of model performance.
- Stay up to date with regulatory developments and industry best practices in quantitative risk management.
Required Skills & Qualifications:
- Degree in a quantitative discipline (Mathematics, Physics, Computer Science, Financial Engineering, or related field).
- Programming skills in C# ; experience with Python, R, or C++ is a plus.
- Experience with regulatory frameworks such as Basel III, FRTB, IFRS 9, CCAR, etc.
- Deep understanding of financial instruments, derivatives pricing models, and risk modeling techniques.
- Strong background in statistical analysis, probability, and numerical methods.
- Excellent analytical, problem-solving, and communication skills.
- Ability to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
- Experience with risk engines and financial libraries.
- Familiarity with regulatory reporting tools and processes.
- Knowledge of machine learning techniques applied to model validation.
- Exposure to cloud-based computation and big data analytics.
This will be a 6 months rolling contract.
Seniority level
- Mid-Senior level
Employment type
- Contract
Job function
- Analyst
- Industries: Investment Banking and Financial Services
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Model Validation Quant employer: Bonhill Partners
Contact Detail:
Bonhill Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Model Validation Quant
✨Tip Number 1
Make sure to brush up on your knowledge of regulatory frameworks like Basel III and FRTB. Understanding these regulations will not only help you in the interview but also show that you're serious about compliance, which is crucial for this role.
✨Tip Number 2
Familiarize yourself with model validation methodologies and be prepared to discuss them in detail. This could include examples of how you've implemented or tested models in previous roles, showcasing your hands-on experience.
✨Tip Number 3
Since programming skills in C# are essential, consider working on a small project or two that demonstrates your proficiency. Being able to showcase your coding abilities can set you apart from other candidates.
✨Tip Number 4
Network with professionals in the investment banking and financial services sectors. Engaging with industry experts can provide insights into the role and may even lead to referrals, increasing your chances of landing the job.
We think you need these skills to ace Model Validation Quant
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Model Validation Quant position. Understand the key responsibilities and required skills, as this will help you tailor your application to highlight relevant experiences.
Highlight Relevant Experience: In your CV and cover letter, emphasize any experience you have with model validation, regulatory frameworks, and programming in C#. Mention specific projects or tasks that demonstrate your analytical and problem-solving skills.
Showcase Technical Skills: Since programming is a crucial part of this role, be sure to detail your proficiency in C# and any additional languages like Python or R. Include examples of how you've used these skills in past roles or projects.
Tailor Your Cover Letter: Craft a personalized cover letter that connects your background to the specific requirements of the Model Validation Quant position. Discuss your understanding of financial instruments and risk modeling techniques, and express your enthusiasm for the role.
How to prepare for a job interview at Bonhill Partners
✨Showcase Your Technical Skills
Make sure to highlight your programming skills in C#, as well as any experience you have with Python, R, or C++. Be prepared to discuss specific projects where you've implemented model validation tools or conducted rigorous testing.
✨Understand Regulatory Frameworks
Familiarize yourself with key regulatory frameworks such as Basel III and FRTB. During the interview, demonstrate your understanding of how these regulations impact model validation and risk management.
✨Prepare for Analytical Questions
Expect questions that assess your analytical and problem-solving abilities. Be ready to discuss statistical analysis, probability, and numerical methods, and provide examples of how you've applied these skills in past roles.
✨Communicate Effectively
Strong communication skills are essential for this role. Practice explaining complex concepts clearly and concisely, especially when discussing model performance and regulatory compliance with non-technical stakeholders.
