Fraud Data Scientist

This is an exciting opportunity for a Fraud Data Scientist to take ownership of fraud analytics and fraud prevention within a growing fintech business. You’ll work on high-impact fraud modelling initiatives, helping to shape how the organisation identifies, prevents, and responds to evolving fraud risks while contributing to a business focused on delivering positive outcomes for its customers.

The Company

This fast-growing fintech has developed an alternative approach to consumer lending, focused on providing a more transparent and predictable borrowing experience. Their innovative model is designed to support customers with managing repayments while helping them build stronger financial habits.

With continued growth and investment in data and analytics, the business is strengthening its Decision Science capability and looking for talented individuals who want to make a visible impact. They are also committed to promoting financial education within local communities and have built a strong reputation for their collaborative and supportive culture.

As a Fraud Data Scientist, you will be responsible for developing and improving the organisation’s fraud prevention capabilities through advanced analytics and machine learning., * Owning fraud analytics and fraud prevention initiatives across the business.

• Developing fraud detection, fraud scoring, and identity verification models.
• Enhancing fraud decisioning through the incorporation of new data sources and innovative modelling approaches.
• Analysing fraud trends, risks, and insights to identify opportunities for improvement.
• Monitoring model performance and recommending enhancements to optimise outcomes.
• Collaborating with underwriting, product, engineering, and wider business teams to implement fraud solutions.
• Translating analytical findings into clear recommendations that drive fraud prevention strategy.
• Supporting the business in identifying and responding to emerging fraud threats, including identity and first-party fraud.

• Strong commercial experience working within fraud analytics, fraud data science, or fraud strategy.
• Experience within a lending business, fintech, banking, payments, e-commerce, or a similar fraud-focused environment.
• Strong Python and SQL skills are essential.
• Experience developing fraud models or applying advanced statistical analysis to fraud prevention challenges.
• Understanding of fraud detection, fraud scoring, identity verification, or fraud strategy frameworks.
• Ability to measure, communicate, and demonstrate the business impact of fraud initiatives.
• Experience working with cross-functional stakeholders to implement analytical solutions.
• Exposure to AWS SageMaker and Databricks would be beneficial., * Python
• SQL