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- Tasks: Develop and manage analytics for counterparty credit risk models in a dynamic team.
- Company: Join Jefferies, a global leader in investment banking and securities with a commitment to diversity.
- Benefits: Enjoy a collaborative culture, opportunities for growth, and a focus on innovation.
- Why this job: Be part of impactful projects that enhance risk management and drive financial insights.
- Qualifications: Master’s degree in a quantitative field; 3-5 years in counterparty credit risk modeling required.
- Other info: Remote work options available; we value diverse perspectives and inclusive practices.
The predicted salary is between 43200 - 72000 £ per year.
Quantitative specialist for developing and managing analytics for counterparty credit risk models. Candidate will join the Risk Analytics group that partakes in model development over the full life-cycle of models: from methodology to design to local implementation and validation. The successful candidate will also provide quantitative risk analysis to support daily counterparty credit risk management.
Responsibilities
- Develop and implement analytics for counterparty credit risk management.
- Build infrastructure to consolidate counterparty credit risk models across systems.
- Perform quantitative research to implement model changes, enhancements and remediations.
- Work with stakeholders across business and functional teams during model development process.
- Create tools and dashboards which can enhance and improve the risk analysis.
- Conduct analysis on existing model short-comings and design remediation plans.
- Maintain, update and back-test risk models.
- Assess the methodologies and processes to identify potential weaknesses and the associated materiality of the risk.
Qualifications
- At least a Master’s Degree in quantitative subject; PhD Degree is a plus.
- Deep understanding of pricing and risk calculations for financial derivatives.
- Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
- At least 3-5 years of experience in counterparty credit risk modeling, in particular experience working with credit simulation engines/models in a CRR and/or an XVA context.
- Strong project management and organizational skills.
- Proficient programming skills in python (other languages such as R is a plus), and strong data handling skills in SQL.
- Excellent written skills (ability to produce well-structured model documentation).
- Excellent oral communication skills to be able to interact effectively with credit risk managers and other model users.
- Knowledge of Numerix and/or Bloomberg a plus.
Contact Detail:
Jefferies LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land European Head of Risk Analytics, SVP
✨Tip Number 1
Familiarise yourself with the latest trends and methodologies in counterparty credit risk modelling. This will not only enhance your understanding but also allow you to engage in meaningful discussions with stakeholders during the interview process.
✨Tip Number 2
Showcase your programming skills, particularly in Python and SQL, by working on relevant projects or contributing to open-source initiatives. This practical experience can set you apart and demonstrate your capability to handle the technical aspects of the role.
✨Tip Number 3
Network with professionals in the risk analytics field, especially those who have experience in counterparty credit risk. Attend industry conferences or webinars to build connections and gain insights that could be beneficial during your application process.
✨Tip Number 4
Prepare to discuss specific examples of how you've identified and remediated model shortcomings in previous roles. Being able to articulate your problem-solving approach will demonstrate your analytical skills and project management capabilities.
We think you need these skills to ace European Head of Risk Analytics, SVP
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quantitative skills and experience in counterparty credit risk modeling. Emphasise your programming skills in Python and SQL, as well as any relevant project management experience.
Craft a Strong Cover Letter: In your cover letter, explain why you are passionate about risk analytics and how your background aligns with the responsibilities outlined in the job description. Mention specific projects or experiences that demonstrate your analytical skills and ability to work with stakeholders.
Showcase Your Technical Skills: Include examples of your work with credit simulation engines/models and any tools or dashboards you've created. This will help illustrate your hands-on experience and technical proficiency, which are crucial for this role.
Highlight Communication Skills: Since the role requires interaction with credit risk managers and other model users, emphasise your excellent written and oral communication skills. Provide examples of how you've effectively communicated complex quantitative concepts to non-technical stakeholders.
How to prepare for a job interview at Jefferies LLC
✨Showcase Your Quantitative Skills
Be prepared to discuss your experience with quantitative models in detail. Highlight specific projects where you've developed or enhanced counterparty credit risk models, and be ready to explain the methodologies you used.
✨Demonstrate Programming Proficiency
Since strong programming skills in Python and SQL are crucial for this role, ensure you can discuss your coding experience. Consider bringing examples of your work or discussing how you've used these languages to solve complex problems.
✨Communicate Effectively
Excellent oral communication skills are essential for interacting with credit risk managers. Practice explaining complex concepts in simple terms, as you may need to convey technical information to non-technical stakeholders.
✨Prepare for Project Management Questions
Given the importance of project management in this role, be ready to discuss your organisational skills. Share examples of how you've managed projects, coordinated with teams, and ensured timely delivery of model developments.
