Harnham
Data Scientist, Credit Risk - FinTech

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Want to build credit risk models that directly influence lending decisions?
Looking for broader ownership than a traditional modelling role offers? Excited by the opportunity to work across modelling, deployment and decision science?
A growing UK FinTech is hiring a Data Scientist to join its Decision Science team. The business has developed an innovative lending model that provides customers with a more transparent and accessible alternative to traditional credit products. With around 100 employees, a strong culture and a collaborative environment, this is an opportunity to have direct influence on how lending decisions are made across the business.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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This role focuses on developing and enhancing credit risk models, with a particular emphasis on scorecards, affordability and decisioning. You'll work across the entire model lifecycle, giving you far greater ownership and commercial exposure than a typical modelling position.
Key Responsibilities
- Develop and improve credit risk scorecards and lending models
- Build solutions using Open Banking and bureau data
- Enhance model performance through feature engineering and analysis
- Support affordability modelling and lending decision optimisation
- Deploy and monitor models across production environments
- Partner with underwriting, finance and credit strategy teams
- Contribute to IFRS9 and wider risk modelling initiatives


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Key Details
- Salary: £55,000-£65,000
- Working Model: Hybrid, 2 days per week in Central London office
- Tech Stack: Python, SQL, Open Banking Data, AWS SageMaker (desirable), Databricks (desirable)
- Visa Sponsorship: Cannot sponsor
Interested? Please apply below.
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