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- Tasks: Lead credit risk strategies and develop predictive models to optimise decision-making.
- Company: Join a dynamic financial solutions provider focused on flexible customer options.
- Benefits: Enjoy a competitive salary, 25 days holiday, private healthcare, and flexible working.
- Why this job: Be part of a growing team with opportunities for long-term progression and impactful work.
- Qualifications: Degree in Data Science or related field; experience in financial services and large data sets required.
- Other info: Travel to Nottingham office once a quarter; fast-paced, evolving environment.
The predicted salary is between 65000 - 70000 £ per year.
Location: England (travel to Nottingham office once a quarter - to business needs)
Salary: £65,000-£70,000 DOE + benefits
Hours: 37.5 Mon-Fri
My client is looking for an experienced Credit Risk Manager to join their growing team. They provide solutions for customers who need flexible and affordable options for their financial needs. Great role for a stand-alone Credit Risk Manager to join their commercial team reporting to the Head of Workforce.
Core Responsibilities of the Credit Risk Manager:
- Extensive hands-on experience with credit scores and scorecards, including development, validation, and monitoring of both custom and bureau-based scoring models.
- Experience working with credit bureau data for credit strategy development, model enhancement, and risk segmentation.
- Design and implement advanced statistical models to assess credit risk, optimise credit scoring, and enhance underwriting strategies.
- Develop and maintain predictive models such as Probability of Default (PD) to forecast customer behaviour and support credit decisioning.
- Perform exploratory data analysis and data cleaning to ensure high-quality inputs for model development.
- Lead A/B testing and controlled experiments to assess the effectiveness of credit strategies and policies.
- Translate complex data insights into actionable recommendations for stakeholders through clear, concise presentations.
Requirements for the Credit Risk Manager role:
- Degree in relevant subject (Data Science, Statistics, Economics or similar degree) (Essential)
- Experience in the Financial Services Industry (Essential)
- Experience working with large data sets (Essential)
- Proficiency in Python, R, SQL or other programming languages (Essential)
- Proficiency in Excel (Essential)
- Ability to communicate technical insights to non-technical audiences effectively (Essential)
- Detail-oriented and process-driven with a focus on continuous improvement (Essential)
- Comfortable working in a fast-paced, evolving environment (Essential)
- Experience working with credit bureau data (highly preferred)
- Experience using Salesforce and data visualisation tools (Preferable)
What we offer:
- Competitive salary - 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.
Please follow the link to apply for this Credit Risk Manager role.
Credit Risk Manager employer: CCA Recruitment Group
Contact Detail:
CCA Recruitment Group 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 risk management. Understanding current methodologies and technologies, especially around predictive modelling and data analysis, will help you stand out during discussions.
✨Tip Number 2
Network with professionals in the financial services industry. Attend relevant conferences or webinars to connect with others in the field, which can lead to valuable insights and potential referrals for the role.
✨Tip Number 3
Prepare to discuss your experience with credit bureau data and statistical modelling in detail. Be ready to share specific examples of how you've used these skills to drive results in previous roles.
✨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 that demonstrate your ability to communicate effectively with 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 your experience in credit risk management, particularly with credit scores and statistical models. Use specific examples that demonstrate your hands-on experience and proficiency in relevant programming languages like Python or R.
Craft a Compelling Cover Letter: In your cover letter, explain why you are the perfect fit for the Credit Risk Manager role. Mention your experience in the financial services industry and how your skills align with the company's needs. Be sure to convey your ability to communicate complex data insights effectively.
Showcase Relevant Projects: If you have worked on projects involving credit bureau data or predictive modelling, include these in your application. Describe your role, the tools you used, and the outcomes of these projects to demonstrate your expertise.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A well-presented application reflects your attention to detail, which is crucial for a role focused on data analysis and risk assessment.
How to prepare for a job interview at CCA Recruitment Group
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in programming languages like Python, R, and SQL during the interview. Be prepared to discuss specific projects where you've used these skills to develop or enhance credit scoring models.
✨Demonstrate Your Analytical Mindset
Prepare examples of how you've performed exploratory data analysis and data cleaning in previous roles. Discuss how these processes contributed to high-quality model development and decision-making.
✨Communicate Clearly
Since the role requires translating complex data insights into actionable recommendations, practice explaining technical concepts in simple terms. This will show your ability to communicate effectively with non-technical stakeholders.
✨Be Ready for Scenario Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about past experiences where you led A/B testing or implemented credit strategies, and be ready to discuss the outcomes and learnings.
