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- Tasks: Join our team to develop and manage counterparty credit risk analytics.
- Company: We're a leading firm focused on inclusive job opportunities for all ages.
- Benefits: Enjoy flexible working options and a supportive corporate culture.
- Why this job: Make an impact in risk management while collaborating with diverse teams.
- Qualifications: Master's degree required; PhD preferred, with 3-5 years in risk modeling.
- Other info: Proficiency in Python and SQL is essential; knowledge of Numerix/Bloomberg is a bonus.
The predicted salary is between 57600 - 84000 £ per year.
Risk Analytics - Counterparty Credit Risk Quantitative Analyst
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.
European Head of Risk Analytics, SVP (London) employer: Jefferies
Contact Detail:
Jefferies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land European Head of Risk Analytics, SVP (London)
✨Tip Number 1
Network with professionals in the risk analytics field, especially those who have experience in counterparty credit risk. Attend industry conferences or webinars to connect with potential colleagues and learn about the latest trends and challenges in the sector.
✨Tip Number 2
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Numerix and Bloomberg. Having hands-on experience or even completing relevant online courses can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your previous projects related to counterparty credit risk modelling in detail. Be ready to explain your thought process, the methodologies you used, and how you overcame any challenges during the project lifecycle.
✨Tip Number 4
Showcase your programming skills by working on personal projects or contributing to open-source projects that involve Python or SQL. This practical experience will not only enhance your skills but also provide concrete examples to discuss during interviews.
We think you need these skills to ace European Head of Risk Analytics, SVP (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in counterparty credit risk modeling and quantitative analysis. Emphasise your programming skills in Python and SQL, as well as any experience with credit simulation engines.
Craft a Strong Cover Letter: In your cover letter, explain why you are the perfect fit for the European Head of Risk Analytics role. Mention specific projects or experiences that demonstrate your analytical skills and project management abilities.
Highlight Your Qualifications: Clearly state your educational background, especially your Master's or PhD in a quantitative subject. Discuss how your academic knowledge applies to the responsibilities outlined in the job description.
Showcase Communication Skills: Since excellent oral and written communication skills are essential, provide examples of how you've effectively communicated complex quantitative concepts to non-technical stakeholders in your previous roles.
How to prepare for a job interview at Jefferies
✨Showcase Your Quantitative Skills
Be prepared to discuss your experience with quantitative models in detail. Highlight specific projects where you've developed or implemented counterparty credit risk models, and be ready to explain the methodologies you used.
✨Demonstrate Your Programming Proficiency
Since strong programming skills in Python are essential for this role, make sure to mention any relevant projects or tools you've built using Python. If you have experience with SQL or R, don't forget to bring that up as well!
✨Prepare for Technical Questions
Expect technical questions related to pricing and risk calculations for financial derivatives. Brush up on key concepts and be ready to solve problems on the spot, as this will demonstrate your analytical capabilities.
✨Communicate Effectively
Given the need for excellent oral communication skills, practice explaining complex concepts in a clear and concise manner. Be prepared to discuss how you've collaborated with stakeholders in previous roles, as this will show your ability to work within teams.
