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- Tasks: Develop and monitor credit scoring models while analysing data to assess risk.
- Company: Join a personal finance lender focused on flexible, affordable short-term finance solutions.
- Benefits: Enjoy 25 days holiday, flexible working options, and private healthcare.
- Why this job: Be part of a growing company with opportunities for long-term progression and a great work-life balance.
- Qualifications: Degree in Data Science, Statistics, or Economics; experience with large datasets and programming languages required.
- Other info: Experience with credit bureau data and Salesforce is a plus but not essential.
The predicted salary is between 36000 - 60000 £ per year.
My client are a personal finance lender who work with a variety of customers who need flexible and affordable short-term finance.
We are seeking a skilled professional with extensive hands-on experience in credit scores and scorecards. The ideal candidate will have expertise in developing, validating, and monitoring both custom and bureau-based scoring models.
Key responsibilities include:
- Working with credit bureau data (e.g., TransUnion, Experian) to develop credit strategies, enhance models, and segment risk.
- Designing and implementing advanced statistical models to assess credit risk, optimize credit scoring, and improve underwriting strategies.
- Developing and maintaining predictive models such as Probability of Default (PD) to forecast customer behaviour and support credit decisioning.
- Performing exploratory data analysis and data cleaning to ensure high-quality inputs for model development.
- Leading A/B testing and controlled experiments to evaluate the effectiveness of credit strategies and policies.
- Translating complex data insights into actionable recommendations for stakeholders through clear, concise presentations.
What you'll need to succeed:
- Degree in a relevant subject such as Data Science, Statistics, Economics, or a similar field.
- Experience in the Financial Services Industry.
- Experience working with large data sets.
- Proficiency in Python, R, SQL, or other programming languages.
- Proficiency in Excel.
- Ability to communicate technical insights effectively to non-technical audiences.
- Detail-oriented and process-driven with a focus on continuous improvement.
- Comfortable working in a fast-paced, evolving environment.
- Experience working with credit bureau data (Preferred / not essential).
- Experience using Salesforce and data visualisation tools (Preferred / not essential).
What you'll get in return:
- Competitive - based on experience.
- 25-days annual holiday (rising by 1 each year to 30) + Bank Holidays.
- A great work-life balance with flexible working options.
- Long-term progression in a growing company.
- Private Healthcare.
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion on your career.
Credit Risk Manager employer: Hays Specialist Recruitment Limited
Contact Detail:
Hays Specialist Recruitment Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Manager
✨Tip Number 1
Familiarise yourself with the latest trends in credit scoring and risk management. Understanding how different scoring models work, especially those from major credit bureaus like TransUnion and Experian, will give you an edge in discussions during interviews.
✨Tip Number 2
Brush up on your programming skills, particularly in Python and R. Being able to demonstrate your proficiency in these languages through practical examples or projects can significantly boost your chances of impressing the hiring team.
✨Tip Number 3
Prepare to discuss your experience with data analysis and model validation. Be ready to share specific instances where you've successfully developed or improved credit risk models, as this will showcase your hands-on expertise.
✨Tip Number 4
Practice translating complex data insights into simple, actionable recommendations. This skill is crucial for the role, so consider preparing a few examples where you've effectively communicated technical information to non-technical stakeholders.
We think you need these skills to ace Credit Risk Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in credit risk management, particularly with credit scores and scorecards. Emphasise your proficiency in programming languages like Python, R, or SQL, as well as your experience with large data sets.
Craft a Strong Cover Letter: In your cover letter, explain why you are a great fit for the Credit Risk Manager role. Mention specific experiences where you've developed or validated scoring models and how you've used credit bureau data to enhance credit strategies.
Showcase Your Analytical Skills: Provide examples of your analytical skills in your application. Discuss any statistical models you've designed or implemented, and how these have contributed to optimising credit scoring or improving underwriting strategies.
Prepare for Technical Questions: Be ready to discuss your technical expertise during the interview process. Prepare to explain complex data insights and how you've communicated these to non-technical stakeholders in previous roles.
How to prepare for a job interview at Hays Specialist Recruitment Limited
✨Know Your Numbers
Brush up on your knowledge of credit scores and scoring models. Be prepared to discuss how you have developed, validated, and monitored these models in your previous roles.
✨Showcase Your Technical Skills
Highlight your proficiency in programming languages like Python, R, and SQL. Be ready to provide examples of how you've used these skills to analyse large data sets and develop predictive models.
✨Communicate Clearly
Practice translating complex data insights into simple, actionable recommendations. You may need to explain technical concepts to non-technical stakeholders, so clarity is key.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about past experiences where you led A/B testing or improved credit strategies, and be ready to discuss the outcomes.
