At a Glance
- Tasks: Lead credit risk analysis and develop strategies for customer management.
- Company: Dynamic UK consumer lender focused on analytics and professional growth.
- Benefits: Competitive salary, hybrid working, and strong learning opportunities.
- Other info: Clear progression paths and exposure to critical projects.
- Why this job: Join a collaborative team and make impactful decisions in credit risk.
- Qualifications: 5+ years in credit risk, strong analytical skills, and experience in consumer lending.
The predicted salary is between 60000 - 66000 £ per year.
A UK-based consumer lender with a growing analytics and credit risk capability. Known for investing in data, modern decision systems, and professional development. Operates with a collaborative culture and clear progression opportunities within analytics.
This is a senior-level credit risk role sitting within an established analytics team, positioned between leadership and junior analysts. The role focuses on existing customer management (ECM) while offering exposure to wider portfolio and acquisition work. Specifically, you can expect to be involved in:
- Developing and enhancing ECM strategy across the lending portfolio.
- Credit limit management, including policy design and customer limit changes.
- Supporting model implementation and the rollout of new behavioural scorecards.
- Portfolio analysis, MI production, and customer trend insight.
- Contributing to cross-team projects, with scope to move into acquisition-focused work over time.
YOUR SKILLS AND EXPERIENCE
- Strong background in consumer lending (e.g., credit cards, personal loans, mortgages).
- Proven experience in ECM or acquisition strategy, including limit or policy work.
- Solid analytical capability with SQL (or a comparable data querying language).
- Ability to communicate insights clearly to both technical and non-technical stakeholders.
- 5+ years' experience in a credit risk or analytics role, operating at a senior level.
THE BENEFITS
- Clear opportunities for progression within a growing analytics team.
- Exposure to wide-ranging, business-critical projects.
- Supportive environment with a strong focus on learning and development.
- Flexible hybrid working model.
THE PROCESS
- Initial 30-minute interview.
- Technical stage including a coding task, presentation, and competency-based discussion with the wider team.
- Final interview with senior stakeholders, including additional technical questions if required.
HOW TO APPLY
Please register your interest via the apply link on this page.
Lead Credit Risk Analyst employer: Harnham
As a Lead Credit Risk Analyst at our UK-based consumer lending company in Leicester, you will thrive in a collaborative culture that prioritises professional development and offers clear progression opportunities within our growing analytics team. With a flexible hybrid working model and a strong focus on learning, you will be involved in impactful projects that shape our credit risk strategies, making this an excellent opportunity for meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Credit Risk Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees at the company on LinkedIn. A friendly chat can give you insider info and might even lead to a referral, which is always a bonus.
✨Tip Number 2
Prepare for your interviews by practising common questions related to credit risk and analytics. We recommend doing mock interviews with friends or using online platforms to get comfortable with your responses.
✨Tip Number 3
Showcase your analytical skills during the interview! Bring examples of past projects where you’ve developed ECM strategies or worked with SQL. This will help you stand out as a candidate who can hit the ground running.
✨Tip Number 4
Don’t forget to follow up after your interviews! A quick thank-you email reiterating your interest in the role can keep you fresh in their minds and show your enthusiasm for the position.
We think you need these skills to ace Lead Credit Risk Analyst
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Credit Risk Analyst role. Highlight your experience in consumer lending and any relevant ECM or acquisition strategy work. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about credit risk and how you can contribute to our analytics team. Keep it concise but impactful – we love a good story!
Show Off Your Analytical Skills:Since this role requires solid analytical capability, make sure to mention your experience with SQL or similar data querying languages. We’re keen to see how you’ve used these skills in past roles to drive results.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the apply link!
How to prepare for a job interview at Harnham
✨Know Your Numbers
As a Lead Credit Risk Analyst, you'll need to demonstrate your analytical skills. Brush up on your SQL and be ready to discuss how you've used data to drive decisions in previous roles. Prepare specific examples of how your analysis has impacted credit limit management or ECM strategies.
✨Communicate Clearly
You’ll be working with both technical and non-technical stakeholders, so practice explaining complex concepts in simple terms. Think about how you can present your insights from past projects in a way that everyone can understand, regardless of their background.
✨Showcase Your Experience
With 5+ years in credit risk or analytics, you’ve got a wealth of experience. Be prepared to discuss your previous roles in detail, especially any work related to consumer lending and policy design. Highlight your contributions to ECM or acquisition strategies and the outcomes of those initiatives.
✨Prepare for Technical Challenges
Expect a coding task during the interview process. Practice common SQL queries and be ready to solve problems on the spot. Familiarise yourself with behavioural scorecards and model implementation, as these are key aspects of the role that may come up in discussions.
