Applied Data Scientist - Fraud Prevention

APPLIED DATA SCIENTIST, FRAUD PREVENTION

£55,000 - £65,000

LONDON (HYBRID)

This is an exciting opportunity to join a growing FinTech with an innovative approach to lending. You'll play a key role in building and improving fraud prevention capabilities, working on high-impact machine learning projects that directly influence customer outcomes, risk strategy, and business performance.

THE COMPANY

Our client is a forward-thinking FinTech with a people-focused culture that prioritises teamwork and continuous development. Data is at the heart of their decision-making, and they are continuing to invest in advanced analytics to support growth and innovation. This role sits within a collaborative data science team where you will have the opportunity to make a tangible impact from day one.

THE ROLE

• Develop and deploy fraud detection, identity verification, and fraud scoring models

• Analyse large and complex datasets to identify fraud trends, risks, and opportunities

• Evaluate new data sources, machine learning techniques, and fraud prevention tools

• Build monitoring and reporting solutions to track model and fraud performance

• Collaborate with Product, Engineering, Risk, and Data teams to deliver business-critical initiatives

• Help shape the future direction of fraud analytics across the organisation

YOUR SKILLS AND EXPERIENCE

• Strong commercial experience in fraud analytics, fraud prevention, or financial crime

• Hands-on experience developing machine learning models using Python

• Strong SQL and data analysis capabilities

• Knowledge of statistical modelling and predictive analytics techniques

• Excellent communication skills with the ability to influence stakeholders

• Experience within fintech, lending, or financial services would be beneficial

SALARY AND BENEFITS

• £55,000 - £65,000 base salary depending on experience

• Annual bonus scheme

• Contributory pension

• Private healthcare

• Hybrid working model - 2 days in office

HOW TO APPLY

Please register your interest by sending your CV through the 'Apply' link.