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- Tasks: Rebuild credit models and enhance analytics for lenders across the UK.
- Company: Leading UK credit data provider with a stable and collaborative culture.
- Benefits: Up to £75k salary, bonus, hybrid work, and standard benefits.
- Why this job: Make a real impact in credit decision-making with ownership of projects.
- Qualifications: 3+ years in data science or credit risk modelling, strong Python and SQL skills.
- Other info: Dynamic role with opportunities for growth in a low-turnover environment.
The predicted salary is between 43200 - 63000 £ per year.
Do you want to rebuild commercial credit models used by lenders across the UK? Have you worked hands-on with SME or corporate lending data end to end? Are you looking for a stable, high-impact analytics role with real ownership?
This organisation is a leading UK credit data provider operating at the heart of the lending ecosystem. They work with banks, fintechs, and commercial lenders to improve credit decision-making through data, analytics, and risk products. The environment is collaborative, stable, and low-turnover, with long-term investment in analytics rather than hype-driven AI.
This is a hybrid Data Scientist / Model Developer position within the commercial lending product team. You will rebuild and enhance core credit products used by lenders, owning models end to end and working with rich commercial datasets.
Key responsibilities- Build and rebuild commercial credit scorecards and decision models
- Develop affordability, segmentation, and forecasting models
- Own models end to end from data exploration to deployment
- Work with commercial datasets such as company registrations and filings
- Contribute to portfolio analytics and ad-hoc analytical projects
- Support the evolution of legacy products into modern solutions
- Salary: up to £75k base + bonus and standard benefits
- Location: London preferred; Leeds or Nottingham considered
- Working model: Hybrid, 3 days onsite (Tues–Thurs)
- Tech stack: Python, SQL
- Visa sponsorship: Not available
- 3+ years’ experience in data science or credit risk modelling
- Proven experience with commercial or business lending data (SME/corporate)
- Strong Python modelling capability; SQL for data access
- Background in credit scorecards, affordability, segmentation, forecasting, or NPV modelling
- STEM degree
- Hands-on, delivery-focused mindset
Interested? Please apply below.
Credit Risk Data Scientist in City of London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in credit risk modelling. Practice common interview questions and be ready to discuss your hands-on experience with SME or corporate lending data.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your work with commercial datasets and any models you've built. This will give potential employers a clear view of your capabilities and how you can contribute to their team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Credit Risk Data Scientist in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Credit Risk Data Scientist. Highlight your experience with commercial lending data and any relevant projects you've worked on. 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 rebuilding credit models and how your background makes you a perfect fit. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Technical Skills: Since this role involves Python and SQL, make sure to mention specific projects where you've used these tools. We want to know how you've applied your technical skills in real-world scenarios, so don’t hold back on the details!
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’re considered for the role. Plus, it gives you a chance to explore more about us and what we do!
How to prepare for a job interview at Harnham
✨Know Your Data Inside Out
Make sure you’re familiar with the types of commercial datasets mentioned in the job description, like company registrations and filings. Brush up on your experience with SME or corporate lending data, as this will be crucial in demonstrating your hands-on knowledge during the interview.
✨Showcase Your Modelling Skills
Prepare to discuss specific projects where you've built or rebuilt credit scorecards and decision models. Be ready to explain your approach, the tools you used (like Python and SQL), and the impact your work had on the business. This will show that you can own models end to end.
✨Understand the Company’s Vision
Research the organisation's role in the lending ecosystem and their focus on stable, long-term analytics. Being able to articulate how your skills align with their mission will demonstrate your genuine interest and fit for the role.
✨Prepare for Technical Questions
Expect technical questions related to credit risk modelling and data science. Brush up on your knowledge of affordability, segmentation, and forecasting models. Practising common data science problems can help you feel more confident when answering these questions.
