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- Tasks: Rebuild commercial credit models and enhance core credit products for lenders.
- Company: Leading UK credit data provider with a focus on analytics and stability.
- Benefits: Up to £75k salary, bonus, hybrid work, and standard benefits.
- Why this job: Make a real impact in the lending ecosystem with ownership of your projects.
- Qualifications: 3+ years in data science, strong Python skills, and experience with commercial lending data.
- Other info: Collaborative environment with long-term investment in analytics.
The predicted salary is between 54000 - 84000 £ 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 London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work with credit risk or data science. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to credit models or data analysis. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python and SQL, and how you've tackled real-world problems in credit risk modelling. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. It shows initiative and helps us get to know you better.
We think you need these skills to ace Credit Risk Data Scientist in 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!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've used Python and SQL in your previous roles, especially in building credit models or working with commercial datasets. This will help us see your hands-on experience.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about credit risk modelling and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of the role!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
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 expertise during the interview.
✨Showcase Your Modelling Skills
Prepare to discuss specific credit scorecards or decision models you've built in the past. Be ready to explain your approach to developing affordability, segmentation, and forecasting models, as well as any challenges you faced and how you overcame them.
✨Demonstrate Ownership and Impact
This role emphasises ownership of models end to end. Think of examples where you took full responsibility for a project, from data exploration to deployment. Highlight how your contributions made a tangible impact on previous projects or teams.
✨Familiarise Yourself with the Company’s Vision
Research the organisation's role in the lending ecosystem and their focus on stable, long-term analytics solutions. Being able to articulate how your values align with theirs will show that you’re not just looking for any job, but that you genuinely want to contribute to their mission.
