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For Companies At a Glance
- Tasks: Validate credit risk models and improve analytics practices using AI and machine learning.
- Company: Join a leading fintech in London with diverse lending portfolios.
- Benefits: Earn up to £80,000 plus an attractive benefits package.
- Why this job: Work with industry experts and influence key risk decisions in a dynamic environment.
- Qualifications: Strong SQL and Python skills, experience in financial services, and a numeric degree required.
- Other info: Hybrid working model available for better work-life balance.
The predicted salary is between 48000 - 80000 £ per year.
Up to £80,000
Hybrid
London
The Company
I am hiring a Model Validation Manager for a top fintech based in London who have multiple portfolios across both unsecured lending and secured lending. You will be working with experts across the industry to validate risk models across the business using AI and Machine learning modelling.
The Role
- Validating Credit Risk models like IFRS9 (PD, EAD, and LGD)
- Using analytics skills to improve credit risk models and model review practices
- Validating wider risk models covering AI, machine learning, reporting, and operational risk models
- Working with senior leadership to present findings of validation exercises
- Using tools like SAS, SQL, R and Python daily
Your skills and experience
- Strong experience with SQL and python
- Strong experience with validating credit risk models
- Experience working in financial services
- Excellent communication skills
- Strong stakeholder management
- A numeric degree from a top university
Benefits
Up to £80,000 + benefits package
HOW TO APPLY
Please register your interest by sending your CV to Sean Tunley via
Credit Risk Model Validation Manager employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Model Validation Manager
✨Tip Number 1
Network with professionals in the fintech industry, especially those who work in credit risk and model validation. Attend relevant meetups or webinars to connect with potential colleagues and learn about the latest trends in AI and machine learning applications in finance.
✨Tip Number 2
Familiarise yourself with the specific credit risk models mentioned in the job description, such as IFRS9 (PD, EAD, and LGD). Being able to discuss these models intelligently during interviews will demonstrate your expertise and enthusiasm for the role.
✨Tip Number 3
Prepare to showcase your analytical skills by discussing past projects where you improved credit risk models or validated them successfully. Use specific examples that highlight your experience with SQL and Python, as these are crucial for the role.
✨Tip Number 4
Research the company’s current portfolios and any recent news related to their operations. This knowledge will not only help you tailor your discussions but also show your genuine interest in the company and its mission during the interview process.
We think you need these skills to ace Credit Risk Model Validation Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with credit risk models, particularly IFRS9, and your proficiency in SQL and Python. Use specific examples to demonstrate your skills in model validation and analytics.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the fintech industry and your ability to work with AI and machine learning. Mention your communication skills and stakeholder management experience, as these are crucial for the role.
Highlight Relevant Experience: In your application, emphasise any previous roles where you validated credit risk models or worked in financial services. Be specific about the tools you used, such as SAS, SQL, R, and Python, to validate models.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects your attention to detail, which is essential for a role in model validation.
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL and Python during the interview. Be prepared to discuss specific projects where you used these tools, especially in validating credit risk models.
✨Understand the Role of AI and Machine Learning
Since the role involves validating models that use AI and machine learning, brush up on these concepts. Be ready to explain how you've applied them in previous roles or how you would approach model validation using these technologies.
✨Prepare for Stakeholder Management Questions
Expect questions about your experience in managing stakeholders. Think of examples where you successfully communicated complex findings to senior leadership or collaborated with different teams.
✨Demonstrate Your Analytical Mindset
As a Model Validation Manager, analytical skills are crucial. Prepare to discuss how you've used analytics to improve credit risk models and any specific methodologies you employed in your past work.
