Data Scientist (Fraud)

A fraud-focused data science role for someone who enjoys hard problems in financial crime and wants their models to reach production. The organisation runs a large digital platform serving millions of customers and merchants and places a strong emphasis on people, learning and knowledge sharing. The role suits a data-driven, curious analyst or scientist with a quantitative background and some experience in payments, risk or fraud, who likes working closely with engineers, product teams and operations colleagues to turn findings into practical protections.

What you'll do

• Prototype, evaluate and help put machine learning models for fraud detection into production, and own their monitoring and retraining
• Design and run experiments to measure the impact of fraud interventions, balancing customer experience against loss reduction
• Size fraud typologies across product lines to inform prioritisation and investment
• Build and maintain anomaly detection systems to surface new fraud patterns early
• Work with fraud operations, engineers, product managers and analysts to turn model outputs into mitigations

What you need

• Degree in a quantitative field such as statistics, mathematics, engineering or computer science
• 3+ years in data science, decision science or risk analytics, ideally within fraud, payments or financial crime
• Hands-on experience deploying machine learning models in production
• Solid grounding in experimentation, statistical inference, model evaluation and feature engineering
• Proficiency in Python and SQL
• Ability to explain technical findings clearly to non-technical stakeholders

Applicants must be based in: United Kingdom.

How to apply

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