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- Tasks: Develop and enhance economic capital and credit risk models while collaborating with a dynamic team.
- Company: Join a leading financial services firm focused on innovative risk analytics.
- Benefits: Competitive salary, professional development, and opportunities for career advancement.
- Other info: Fast-paced environment with opportunities to work on diverse projects and grow your career.
- Why this job: Make a real impact in finance by improving risk models and driving strategic initiatives.
- Qualifications: Experience in statistical models and strong programming skills, especially in Python.
The predicted salary is between 60000 - 80000 £ per year.
This role is part of the Portfolio Credit Analytics sub-team of Risk Analytics. The team is responsible for the development and maintenance of economic capital models, portfolio credit risk models, scenario based stress testing models, product specific stress testing models, and rating models. The candidate will participate in the development and maintenance of economic capital models, stress expected loss models, and other stress testing models. The candidate will work with other colleagues in the team, in the wider Risk Analytics Group, and in the Risk area, in particular credit risk managers and model validation.
KEY RESPONSIBILITIES
- Developing, maintaining and improving economic capital models and other models the team is responsible for such as ECL stress testing.
- Designing and running model validation tests, for both model assumptions and implementation.
- Investigating issues and proposing changes where there are model weaknesses.
- Specifying and testing system changes to implement improvements.
- Ad-hoc projects as required, including collaboration with business, Credit Risk Management and Model Validation.
- Investigating issues relating to the Credit Risk Models.
- Proactively contributing to wider Risk function initiatives and projects.
Required Skills
- Previous experience with statistical models in finance.
Desirable
- Previous experience in Economic Capital models, including PD, LGD and EAD modelling.
- Previous experience in Portfolio Credit Risk modelling.
Work Experience:
- 2 to 5 years experience in a Financial Services firm.
- Strong knowledge in statistics.
- Knowledge of advanced programming languages (Python).
Desirable
- Portfolio Credit Risk modelling.
- Knowledge of basic theory of default modelling.
Education / Qualifications:
- Highly numerate education (Maths, Statistics, Engineering, Computer Science) at MSc level or above.
- Excellent communication skills with the ability to adjust to different audiences.
- Highly motivated and innovative, able to work on own initiative.
- Excellent accuracy and attention to detail with an analytical mind-set.
- Good team player with professional attitude.
- Good time management and ability to prioritise.
- Ability to manage large workloads and tight deadlines, balancing urgent tasks and longer term projects.
- Strong decision making skills, the ability to demonstrate sound judgement.
- Strong problem solving skills.
- Strong numerical skills.
Portfolio Credit Risk Modelling Quant - AVP in London employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Portfolio Credit Risk Modelling Quant - AVP in London
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and risk analytics space on LinkedIn. Join relevant groups and engage in discussions. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Make sure you can talk confidently about economic capital models and stress testing. We recommend running through some practice questions with a friend or using online resources to sharpen your knowledge.
✨Tip Number 3
Showcase your projects! If you've worked on any relevant models or analyses, be ready to discuss them in detail. Bring along examples of your work or even a portfolio if you have one. This will help you stand out and demonstrate your hands-on experience.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Portfolio Credit Risk Modelling Quant - AVP in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with statistical models and any relevant projects you've worked on in finance.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for the Portfolio Credit Risk Modelling Quant role. Share specific examples of your work with economic capital models or stress testing models to grab our attention.
Show Off Your Technical Skills: Since we're looking for someone with strong programming skills, don't forget to mention your proficiency in Python and any other advanced programming languages you know. Give us a glimpse of how you've used these skills in your previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen on joining our team!
How to prepare for a job interview at Morgan McKinley
✨Know Your Models Inside Out
Make sure you’re well-versed in the economic capital models and stress testing models mentioned in the job description. Brush up on your knowledge of PD, LGD, and EAD modelling, as well as any statistical models you've worked with. Being able to discuss these confidently will show that you’re not just familiar with the concepts but can also apply them.
✨Showcase Your Programming Skills
Since knowledge of advanced programming languages like Python is essential, be prepared to discuss your experience with coding. Bring examples of how you've used programming to solve problems or improve models in your previous roles. If possible, have a small project or code snippet ready to demonstrate your skills.
✨Prepare for Scenario-Based Questions
Expect questions that test your problem-solving abilities and decision-making skills. Think of scenarios where you had to investigate model weaknesses or propose changes. Use the STAR method (Situation, Task, Action, Result) to structure your answers clearly and effectively.
✨Communicate Effectively
Given the importance of communication in this role, practice explaining complex concepts in simple terms. Be ready to adjust your communication style based on who you’re speaking to, whether it’s a technical colleague or a credit risk manager. This will demonstrate your ability to collaborate within the team and across departments.