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- Tasks: Oversee validation of credit risk models and develop insightful reports for stakeholders.
- Company: Leading FinTech firm in London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a significant impact in the FinTech industry.
- Qualifications: Experience in model validation using Python and knowledge of unsecured lending.
- Other info: Ideal for mid-senior level analysts looking to advance their careers.
The predicted salary is between 48000 - 72000 £ per year.
A leading FinTech firm in London is hiring a Lead Model Validation Analyst to oversee validation of all models, particularly in credit risk. The ideal candidate will validate IFRS9 and credit scorecard models and develop reports for senior stakeholders.
Applicants should have experience with model validation in Python and a background in unsecured lending. This full-time role seeks a mid-senior level analyst who can effectively communicate findings to non-technical audiences.
Lead Credit Risk Model Validator | IFRS9 & Scorecards in England employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Credit Risk Model Validator | IFRS9 & Scorecards in England
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech space, especially those who work with credit risk models. A friendly chat can open doors and give you insights that might just land you that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a presentation that highlights your experience with model validation, especially in Python. This will help you stand out when discussing your qualifications with potential employers.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing answers to common questions about IFRS9 and scorecard models. Being able to explain complex concepts simply will impress those non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Lead Credit Risk Model Validator | IFRS9 & Scorecards in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with model validation, especially in Python and unsecured lending. We want to see how your skills align with the role of Lead Credit Risk Model Validator.
Showcase Your Communication Skills: Since you'll be communicating findings to non-technical audiences, include examples in your application that demonstrate your ability to simplify complex concepts. We love clear communicators!
Be Specific About Your Experience: When detailing your past roles, focus on specific projects or models you've validated. We’re looking for concrete examples that show your expertise in IFRS9 and credit scorecards.
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 don’t miss any important updates from us!
How to prepare for a job interview at Harnham
✨Know Your Models Inside Out
Make sure you’re well-versed in the specifics of IFRS9 and credit scorecard models. Brush up on your model validation techniques, especially in Python, as you’ll need to demonstrate your expertise during the interview.
✨Prepare for Technical Questions
Expect to face technical questions about model validation processes and methodologies. Practise explaining complex concepts in simple terms, as you’ll need to communicate findings to non-technical stakeholders effectively.
✨Showcase Your Unsecured Lending Experience
Highlight any relevant experience you have in unsecured lending. Be ready to discuss how this background informs your approach to model validation and how it can benefit the firm’s objectives.
✨Bring Data-Driven Insights
Prepare to discuss past projects where you’ve validated models and the impact of your findings. Use data-driven examples to illustrate your analytical skills and how they can contribute to the firm’s success.
