Fraud Data Scientist

Harnham - Data and Analytics Recruitment; Greater London; Hybrid; GBP 55,000 - 65,000; Full time

Job summary

Unknown is seeking a Fraud Data Scientist in London to own fraud analytics and drive prevention initiatives within a growing fintech environment. You will develop fraud detection and scoring models, verify identities, and enhance decisioning with new data sources.

The role focuses on identifying evolving fraud risks and delivering high-impact analytics to protect customers and the business, with a hybrid work pattern and close collaboration across teams.

Qualifications

• 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.
• Experience within fraud analytics, fraud data science, or fraud strategy.

Responsibilities

• 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.

Skills

Python

SQL

Fraud analytics

Fraud data science

Fraud strategy

Cross-functional collaboration

Model development

Tools

AWS SageMaker

Databricks

Job description

Fraud Data Scientist

London (Hybrid, 2 Days per Week) | £55,000 - £65,000

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.

Key responsibilities include:

• 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.

Your Skills & Experience

• 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.