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- Tasks: Lead the development of advanced credit risk models for wholesale portfolios.
- Company: Join Crisil, a leader in credit risk analysis and modelling.
- Benefits: Enjoy a full-time role with opportunities for mentorship and professional growth.
- Why this job: Make a significant impact on credit risk modelling while collaborating with diverse teams.
- Qualifications: Expertise in SAS, Python, R, SQL, and knowledge of IRB standards required.
- Other info: Located in London; EU work permit is necessary.
The predicted salary is between 72000 - 108000 £ per year.
We are seeking an experienced Lead Model Developer with exceptional expertise in credit risk modeling, especially the wholesale portfolio (banks, corporate, specialized lending, real estate, non-banking). The ideal candidate will bring deep domain knowledge and advanced technical skills to drive sophisticated credit risk modeling initiatives across wholesale portfolios.
Location: London
Employment Type: Full-time
Key Responsibilities:
- Lead end-to-end development of advanced credit risk models, including PD, EAD, LGD models compliant to IRB Standards from inception to IRB accreditation.
- Significant contribution to the IRB accreditation process.
- Conduct comprehensive data preparation, preprocessing using tools including SAS, Python, R, and SQL.
- Design, build, calibrate and implement robust credit risk models across wholesale portfolios with rigorous User Acceptance Testing (UAT).
- Collaborate with cross-functional stakeholders to analyze, interpret, and communicate complex model results and insights.
- Model documentation, Business Requirements Documents (BRD), Regulatory compliance documentation.
- Drive continuous model improvement through: Identifying optimization opportunities; Implementing advanced modeling techniques; Enhancing model performance and predictive accuracy.
- Provide mentorship and technical guidance to junior team members, fostering a culture of knowledge sharing and professional development.
Required Qualifications:
- Proven expertise in modeling across wholesale/LDP credit portfolios.
- Advanced proficiency in: SAS, Python, R, SQL.
- Strong knowledge of capital models (IRB approach).
- Exceptional analytical and problem-solving skills.
- Excellent written and verbal communication abilities.
Preferred Qualifications:
- Advanced degree in Statistics, Mathematics, Economics, or related field.
- Professional certifications in risk management or financial modeling.
- Experience with machine learning and advanced statistical modeling techniques.
- Knowledge of Basel regulatory requirements.
Technical Skills:
- Programming: SAS, Python, R, SQL.
- Regulatory Knowledge: IRB (Must).
Director - Credit Risk Modeller ( IRB ) employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Director - Credit Risk Modeller ( IRB )
✨Tip Number 1
Network with professionals in the credit risk modelling field. Attend industry conferences, webinars, or local meetups to connect with others who work in similar roles. This can help you gain insights into the latest trends and potentially lead to referrals.
✨Tip Number 2
Showcase your technical skills by working on relevant projects or contributing to open-source initiatives. Having a portfolio that demonstrates your proficiency in SAS, Python, R, and SQL will make you stand out to hiring managers.
✨Tip Number 3
Stay updated on regulatory changes and advancements in credit risk modelling techniques. Being knowledgeable about Basel requirements and recent developments in machine learning can give you an edge during interviews.
✨Tip Number 4
Prepare for interviews by practising how to explain complex model results and insights clearly. Being able to communicate effectively with cross-functional stakeholders is crucial for this role, so focus on honing your verbal communication skills.
We think you need these skills to ace Director - Credit Risk Modeller ( IRB )
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in credit risk modeling, particularly with wholesale portfolios. Emphasise your proficiency in SAS, Python, R, and SQL, as well as any relevant certifications or advanced degrees.
Craft a Compelling Cover Letter: In your cover letter, explain why you are the ideal candidate for the Director - Credit Risk Modeller position. Discuss your experience with IRB standards and your contributions to model development and accreditation processes.
Showcase Technical Skills: Clearly outline your technical skills related to credit risk modeling. Provide specific examples of projects where you have used advanced statistical techniques or machine learning to improve model performance.
Highlight Leadership Experience: Since this role involves mentoring junior team members, be sure to include any leadership or mentorship experiences you have. Describe how you fostered knowledge sharing and professional development in previous roles.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in SAS, Python, R, and SQL. Bring examples of past projects where you successfully developed credit risk models, highlighting your technical expertise and problem-solving abilities.
✨Understand the IRB Standards
Familiarise yourself with the IRB accreditation process and Basel regulatory requirements. Demonstrating a solid understanding of these standards will show that you are well-prepared for the role and can contribute effectively from day one.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to handle real-world challenges in credit risk modelling. Prepare to discuss how you would approach model development, data preparation, and optimisation opportunities in various scenarios.
✨Emphasise Collaboration and Mentorship
Highlight your experience working with cross-functional teams and mentoring junior colleagues. Discuss how you foster a culture of knowledge sharing and professional development, as this is crucial for the role.
