Data Scientist – Fraud

Overview

In this role you will build market-leading fraud models for Equifax UK, leveraging diverse data sources and cloud tooling. You will work with cross-functional teams to deliver AI/ML-driven scoring solutions that protect consumers and businesses. You’ll explore feature engineering, segmentation and challenger experiments to maximize predictive power, while aligning with risk and regulatory guidelines. This is a chance to shape next-generation fraud analytics within a collaborative, growth-focused environment.

Pay / Benefits

• contributory pension
• life cover
• income protection
• healthcare
• 26 days holiday
• birthday day off

Responsibilities

• Develop market-leading consumer and commercial fraud models and related indicators
• Combine multiple data sources (consumer bureau data, postcode insights, open source and partnerships data) to enhance predictive power
• Apply traditional modeling (logistic regression) and modern AI/ML methods (gradient boosting, random forests, clustering)
• Utilise cloud-based technologies and test-and-learn champion/challenger approaches for model development
• Create new features/attributes to improve model performance and support other analytical products
• Perform segmentation to optimise model and score performance across sub-populations
• Collaborate with Product Managers, Model Risk Management, Pre-Sales, Compliance and Technology to deliver scores and products
• Document model development for peer review and Model Risk Management
• Share best practices with Data Scientists globally and maintain adherence to development policies and procedures

Key requirements

• Experience using credit bureau data in statistical fraud models
• Extensive experience developing statistical models and scores in fraud (consumer and commercial)
• Numerate with a relevant degree (2:1 or above)
• Proficiency with analytical tools (Python, SAS, BigQuery, Jupyter, SQL)
• Experience developing regression models and scores (logistic)
• Experience handling large/complex datasets and creating master datasets
• Experience across fraud types (consumer, commercial, AML, KYC)
• Excellent communication and ability to work with minimal supervision
• Understanding of regulatory landscape affecting consumer and commercial credit

• team player
• effective communicator
• creative and innovative thinker
• Python
• SAS
• BigQuery

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