More jobs:
Analytics Manager; Card Fraud
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-06-18
Listing for:
Capital on Tap
Full Time
position Listed on 2026-06-18
Job specializations:
-
Finance & Banking
FinTech, Banking & Finance -
IT/Tech
FinTech, Banking & Finance, Data Analyst
Job Description & How to Apply Below
Location: Greater London
Requirements
- A strong data analyst background in a fintech or digital lending environment. You know what SMB or consumer transaction data looks like and you're comfortable. working with messy, high-volume datasets
- SQL you can actually use. CTEs, window functions, the difference between WHERE and HAVING. You'll be tested on this at case study stage
- A genuine builder instinct. You don't wait to be told there's a problem. You find it in the data and you fix it
- Experience working end-to-end on analytical problems. Not handing logic to a tech team. You own it through to deployment
- Comfortable in a small, fast-moving team where the answer isn't always obvious and you have to work it out yourself
- (Desirable) Direct experience working in card fraud - ideally within a bank, card issuer, or fintech operating on the issuing side
- (Desirable) Hands-on familiarity with card fraud systems and the data that comes with them (Visa fraud platforms, CNP fraud, 3DS/SCA, PSD2 compliance)
- (Desirable) Experience with APP fraud or faster payment fraud systems is a strong bonus
- We're looking for a Senior/Lead Card Fraud Data Analyst/ Analytics Manager to join our Fraud team
- This is a hands-on, high-ownership role - you'll take direct responsibility for our fraud systems end-to-end, from onboarding fraud through to card fraud, and play a central part in building the capabilities we need as we launch new products
- Write complex SQL queries to interrogate transaction and customer data, identify fraud signals, and surface emerging attack patterns
- Design and build fraud detection rules from scratch, set thresholds based on data, and iterate based on live performance
- Own rules end-to-end. You spot the pattern, you build the detection, you monitor the outcome
- Work across card and lending data to understand how our customers behave and where fraud risk sits in our specific product set
- Contribute to fraud strategy as the team grows, including input into ML-based detection further down the line
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