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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 initiatives.
- Why this job: Make a real impact in finance by improving critical risk models and driving innovation.
- 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 City of 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 City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and risk analytics space. Attend industry events or webinars, and don’t be shy about introducing yourself. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with economic capital models and stress testing. This can be a great conversation starter during interviews and helps us see your practical experience in action.
✨Tip Number 3
Prepare for those tricky interview questions! Brush up on your knowledge of statistical models and be ready to discuss your previous experiences in detail. We want to hear how you’ve tackled challenges in credit risk modelling.
✨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, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Portfolio Credit Risk Modelling Quant - AVP in City of 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. We want to see how you fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about Portfolio Credit Risk Modelling and how your background makes you a great fit for us. Don't forget to mention your programming skills and any specific models you've worked on.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We love candidates who can demonstrate strong decision-making and problem-solving abilities, especially in the context of credit risk models.
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 you’re keen on joining our team at StudySmarter!
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. Be ready to discuss your previous experience with statistical models in finance, especially any work you've done with PD, LGD, and EAD modelling.
✨Brush Up on Your Programming Skills
Since knowledge of advanced programming languages like Python is crucial, take some time to review relevant coding concepts and be prepared to demonstrate your skills. You might even want to bring examples of your past projects that showcase your programming prowess.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and decision-making abilities. Think of specific instances where you identified model weaknesses or proposed improvements, and be ready to explain your thought process clearly.
✨Show Off Your Team Spirit
This role requires collaboration with various teams, so highlight your teamwork experiences. Share examples of how you’ve worked effectively with credit risk managers or in model validation, and emphasise your ability to communicate complex ideas to different audiences.