Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead credit risk strategies and develop predictive models to drive business growth.
- Company: Join a fast-growing fintech revolutionising financial access for underserved communities.
- Benefits: Enjoy competitive salary, flexible hours, 25+ days holiday, and private healthcare.
- Why this job: Make an impact in financial inclusion while working with cutting-edge analytics.
- Qualifications: Degree in Data Science or related field; 8+ years in Financial Services required.
- Other info: Hybrid working options available; career growth in a scaling fintech.
The predicted salary is between 45000 - 65000 £ per year.
Are you a data-driven Credit Risk professional looking to make an impact in the fintech space? Join a fast growing lending company that's revolutionizing access to financial services for underserved communities.
The Role: As our Credit Risk Manager, you'll lead the development and optimization of our credit decisioning strategies, leveraging advanced analytics to drive business growth while maintaining robust risk management frameworks.
Key Responsibilities:
- Drive Credit Innovation & Risk Strategy:
- Shape the future of credit decisioning through custom scorecard development and validation
- Partner with major credit bureaus (TransUnion, Experian) to enhance risk segmentation
- Architect advanced statistical models that revolutionize our credit risk assessment
- Build next-generation Probability of Default (PD) models
- Transform raw data into powerful predictive insights
- Pioneer A/B testing frameworks to optimize credit strategies
- Turn complex credit data into clear, actionable business strategies
- Lead data quality initiatives to ensure model excellence
- Present game-changing insights to key decision-makers
You’ll thrive in this role if you love:
- Solving complex credit risk challenges
- Working with cutting-edge predictive modeling
- Translating data science into business impact
- Driving innovation in financial inclusion
Must-Have Qualifications:
- Degree in Data Science, Statistics, Economics or related field
- Minimum 8+ Financial Services industry experience
- Minimum 5+ experience in UK & Right to work in UK
- Strong programming skills (Python, R, SQL)
- Advanced Excel proficiency
- Experience with large-scale data analysis
- Proven track record in credit risk modelling
Must-Have Expertise:
- Data Science, Statistics, or Economics degree - your foundation in quantitative excellence
- Financial Services background - you understand the industry's pulse (Essential)
- Strong programming skills (Python, R, SQL) - or other programming languages (Essential)
- Excel champion - (Essential)
- Ability to communicate technical insights to non-technical audiences effectively (Essential)
- Process optimisation mindset - you’re always looking for better ways (Essential)
- Adaptable performer - you thrive in dynamic environments (Essential)
Bonus Points For:
- Credit bureau data experience - (highly preferred)
- Salesforce & data visualization tools - (Preferable)
Why Join Us:
- Competitive Salary
- True work-life balance with flexible hours
- 25 days holiday (increasing to 30) + Bank Holidays
- Private Healthcare
- Hybrid working options
- Career growth in a scaling fintech
Ready to shape the future of inclusive lending? Apply now to join our innovative team!
Credit Risk Manager employer: QuidMarket Loans
Contact Detail:
QuidMarket Loans Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Manager
✨Tip Number 1
Network with professionals in the fintech and credit risk sectors. Attend industry events, webinars, or local meetups to connect with potential colleagues and learn about the latest trends in credit risk management.
✨Tip Number 2
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, R, SQL, and data visualisation tools. Consider taking online courses or certifications to enhance your skills and demonstrate your commitment to the role.
✨Tip Number 3
Prepare to discuss your experience with predictive modelling and credit risk strategies in detail during interviews. Be ready to share specific examples of how you've successfully implemented these strategies in previous roles.
✨Tip Number 4
Research the company’s mission and values, especially their focus on financial inclusion. Be prepared to articulate how your personal values align with theirs and how you can contribute to their goals in the fintech space.
We think you need these skills to ace Credit Risk Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in credit risk management and data science. Focus on relevant roles where you've developed credit decisioning strategies or predictive models, and quantify your achievements to demonstrate impact.
Craft a Compelling Cover Letter: In your cover letter, express your passion for fintech and financial inclusion. Discuss how your skills in programming (Python, R, SQL) and your experience with large-scale data analysis make you a perfect fit for the role.
Showcase Your Technical Skills: Clearly outline your technical skills in your application. Mention your proficiency in Excel and any experience with credit bureau data or data visualisation tools, as these are highly relevant to the position.
Prepare for Interviews: Be ready to discuss your previous projects related to credit risk modelling and predictive analytics. Prepare examples that showcase your ability to communicate complex data insights to non-technical stakeholders.
How to prepare for a job interview at QuidMarket Loans
✨Showcase Your Data Skills
As a Credit Risk Manager, your ability to work with data is crucial. Be prepared to discuss your experience with programming languages like Python, R, and SQL, and provide examples of how you've used these skills to develop credit models or analyse large datasets.
✨Demonstrate Your Industry Knowledge
Make sure you understand the financial services landscape, especially in the UK. Familiarise yourself with current trends in credit risk management and be ready to discuss how they impact decision-making in fintech.
✨Prepare for Technical Questions
Expect to face technical questions related to credit risk modelling and predictive analytics. Brush up on concepts like Probability of Default (PD) models and be ready to explain your approach to building and validating these models.
✨Communicate Clearly
You'll need to present complex data insights to non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the business impact of your work and how it aligns with the company's goals.
