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- Tasks: Validate and approve financial models, assess risks, and communicate findings to stakeholders.
- Company: Join Jefferies, a leading global investment bank known for its innovative approach.
- Benefits: Enjoy competitive pay, opportunities for remote work, and a dynamic team environment.
- Why this job: Be part of a crucial team that shapes risk management strategies and drives innovation.
- Qualifications: MSc or PhD in a quantitative field; strong Python skills and teamwork abilities required.
- Other info: Ideal for those passionate about finance and model validation in a fast-paced setting.
The predicted salary is between 48000 - 72000 £ per year.
The primary mandate of the Model Validation Team is to manage risk that arises from models used in the firm throughout its range of businesses, including models used for derivatives valuation, market and credit risk management, liquidity, and capital computations. The team is responsible for independently reviewing models for validity, theoretical consistency and implementation accuracy, as well as assessing the risk associated with model choice.
Key Responsibilities:
- Perform independent validation and approval of models, including raising and managing model validation findings.
- Conduct annual review and revalidation of existing models.
- Provide effective challenge to model assumptions, mathematical formulation, and implementation.
- Assess and quantify the model risk arising from model limitations, to inform stakeholders of their risk profile and development of compensating controls.
- Contribute to strategic, cross-functional initiatives within the model risk team.
- Oversee ongoing model performance monitoring, including benchmarking, process verification and outcome analysis performed by model developers.
- Communicate the results of model validation activities, model limitations and uncertainties to the key stakeholders and management.
- Contribute to automation/AI efficiency initiatives.
Qualifications:
- MSc or preferably PhD in a quantitative field (physics, mathematics, computer science, financial engineering, etc.).
- Understanding of all aspects of the VaR computation framework and Counterparty Credit Risk modelling.
- Strong Python coding skills preferable.
- Strong communication skills with the ability to find practical solutions to challenging problems.
- Teamwork and collaboration skills a must.
- Experience with risk model validation and/or development of Internal Liquidity Stress Test models.
Quantitative Analyst, Model Validation, AVP employer: Jefferies
Contact Detail:
Jefferies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst, Model Validation, AVP
✨Tip Number 1
Familiarise yourself with the specific models and methodologies used in model validation, particularly those related to derivatives valuation and risk management. This knowledge will help you engage in meaningful discussions during interviews and demonstrate your understanding of the role.
✨Tip Number 2
Brush up on your Python coding skills, as strong programming abilities are essential for this position. Consider working on personal projects or contributing to open-source initiatives that involve quantitative analysis to showcase your skills.
✨Tip Number 3
Network with professionals in the field of quantitative analysis and model validation. Attend industry conferences, webinars, or local meetups to connect with others and gain insights into the latest trends and challenges in the industry.
✨Tip Number 4
Prepare to discuss your experience with risk model validation and any relevant projects you've worked on. Be ready to explain how you approached challenges and what solutions you implemented, as this will highlight your problem-solving skills and teamwork capabilities.
We think you need these skills to ace Quantitative Analyst, Model Validation, AVP
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative analysis, model validation, and risk management. Emphasise your educational background, particularly if you have an MSc or PhD in a quantitative field.
Craft a Strong Cover Letter: In your cover letter, clearly articulate your understanding of the role and how your skills align with the responsibilities outlined in the job description. Mention your Python coding skills and any experience with risk model validation.
Showcase Communication Skills: Since strong communication skills are essential for this role, provide examples in your application that demonstrate your ability to convey complex information effectively. This could be through previous work experiences or projects.
Highlight Teamwork Experience: The job requires teamwork and collaboration, so include specific instances where you've successfully worked in a team setting. This will show your ability to contribute to cross-functional initiatives within the model risk team.
How to prepare for a job interview at Jefferies
✨Showcase Your Technical Skills
As a Quantitative Analyst, you'll need to demonstrate your strong Python coding skills. Be prepared to discuss specific projects where you've applied your programming knowledge, and consider bringing examples of your work or code snippets to showcase your abilities.
✨Understand Model Validation Processes
Familiarise yourself with the model validation processes relevant to the role. Be ready to explain how you would approach validating models, including how you would assess their theoretical consistency and implementation accuracy.
✨Communicate Clearly and Effectively
Strong communication skills are essential for this role. Practice explaining complex quantitative concepts in simple terms, as you'll need to convey model limitations and uncertainties to stakeholders who may not have a technical background.
✨Demonstrate Teamwork and Collaboration
The role requires effective collaboration within the model risk team. Prepare examples of past experiences where you've successfully worked in a team setting, highlighting your ability to contribute to cross-functional initiatives and support your colleagues.
