Harnham
Founding Data Scientist - Credit Risk Start-up

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Want to shape the future of responsible lending at an early-stage fintech? Enjoy owning credit models from development through to production? Looking for the autonomy to influence lending strategy rather than just build models?
A fintech start-up that's rethinking personal lending through salary-linked loans, creating a fairer, more flexible borrowing experience centred around affordability rather than traditional credit scoring.
With a live product, positive cash flow and fresh funding on the horizon, they're entering an exciting growth phase and are looking for a Senior Data Scientist to play a pivotal role in scaling their credit decisioning capability.
The Role
You'll join a small, high-impact team reporting directly to the VP of Credit, taking ownership of the company's credit risk modelling and decisioning capability.
Reasons to use Rodeo
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?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities:
- Building and improving credit risk and decisioning models using Open Banking, bureau and internal lending data
- Developing scorecards and machine learning models to support underwriting decisions
- Deploying, monitoring and maintaining models within AWS production environments
- Analysing portfolio performance, arrears, defaults and customer behaviour
- Working closely with Product, Engineering and Risk to operationalise models and improve lending strategies
You'll ideally bring:
- Commercial experience building credit risk or decisioning models within lending (insurance backgrounds may also be considered)
- Strong experience with scorecards, logistic regression and/or machine learning models
- Good understanding of how models influence real lending decisions and commercial outcomes
- Experience deploying and maintaining models within production environments
- Strong Python, SQL and AWS experience (particularly SageMaker and Lambda)
- Comfortable working in a fast-moving, hands-on environment with high ownership
- Excellent communication skills with both technical and business stakeholders


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What's on Offer?
- Salary up to £70,000
- Founding equity
- Hybrid working (2 days per week in Central London)
Apply below if interested.
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