Harnham
Data Scientist, Fraud - Alternative Credit FinTech

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Data Scientist - Fraud Analytics
Want to own fraud analytics in a growing FinTech? Interested in building fraud models that directly influence customer decisions? Looking for a role with real ownership, visibility, and impact?
A high-growth UK FinTech is hiring a Data Scientist to help shape the future of its fraud capability. The business has built a unique lending model that provides customers with a more predictable and accessible way to borrow, while also supporting financial education initiatives across the UK. With around 100 employees and a collaborative culture, this is an opportunity to join a business where your work will be highly visible and commercially impactful. You'll work closely with underwriting, product, engineering and leadership teams to improve fraud prevention and decisioning.
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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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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.
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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 Data Scientist position focuses on fraud analytics, fraud modelling and fraud prevention across the full customer lifecycle. The role offers significant ownership, exposure to production systems and the opportunity to influence how the business detects and prevents fraud at scale.
Key Responsibilities
- Develop and enhance fraud detection and fraud scoring models
- Design and implement identity verification and fraud prevention solutions
- Analyse fraud trends and deliver actionable business insights
- Introduce new data sources and features to improve model performance
- Collaborate with Product and Engineering to deploy production fraud models
- Drive measurable reductions in fraud through analytics and machine learning
- Support wider data science initiatives across decisioning and risk functions


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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, AWS SageMaker (desirable), Databricks (desirable)
- Visa Sponsorship: Cannot sponsor
Interested? Please apply below.
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