About the Company

We are a technology-driven financial services company delivering digital payment solutions and financial products to customers and businesses across Europe. Through data analytics, predictive modelling, and intelligent risk management, we aim to protect customers, reduce financial losses, and maintain secure payment environments.

Role Overview

We are seeking a Data Scientist specialising in fraud detection and prevention to analyse complex financial datasets and develop predictive models that identify suspicious transactions and fraudulent behaviour. You will work closely with fraud investigators, risk analysts, data engineers, and software developers to transform data into actionable insights and improve the effectiveness of fraud prevention strategies.

Key Responsibilities

• Analyse payment transactions, customer behaviour, and account activity to identify fraud patterns and emerging threats.
• Develop and validate predictive models for transaction fraud, account takeover, and suspicious financial activity.
• Apply statistical analysis, supervised learning, and anomaly detection techniques to identify unusual behaviour.
• Perform feature engineering and exploratory data analysis on large transaction datasets.
• Evaluate model performance using precision, recall, F1-score, ROC-AUC, and fraud-loss indicators.
• Investigate false positives and false negatives to improve detection accuracy.
• Develop dashboards and analytical reports to communicate fraud trends and risk indicators.
• Collaborate with fraud operations teams to incorporate investigation findings into analytical models.
• Monitor changes in fraud patterns and recommend improvements to existing detection rules and models.
• Support the implementation of data-driven fraud prevention strategies while maintaining appropriate privacy and governance standards.

Requirements and Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• At least 3 years of experience in data science, fraud analytics, risk analytics, or predictive modelling.
• Strong proficiency in Python and libraries such as pandas, NumPy, scikit-learn, and XGBoost.
• Advanced SQL skills and experience working with large structured datasets.
• Knowledge of classification algorithms, anomaly detection, statistical inference, and feature engineering.
• Experience evaluating models using imbalanced datasets and fraud-specific performance metrics.
• Familiarity with data visualisation tools such as Power BI, Tableau, or Looker.
• Understanding of payment fraud, card transactions, digital banking, or financial crime patterns is an advantage.
• Knowledge of GDPR, data privacy, and responsible AI practices.
• Strong analytical, problem-solving, and communication skills.

What We Offer

• Competitive salary based on qualifications and experience.
• Flexible hybrid or remote working arrangements, subject to company policy.
• Opportunity to work with large-scale financial datasets and modern analytical tools.
• Professional development and continuous learning opportunities.
• Collaborative work with experienced data scientists, engineers, and fraud specialists.
• Opportunities to contribute directly to fraud reduction and customer protection initiatives.

Application Instructions

Submit an up-to-date CV highlighting your experience in data science, fraud analytics, predictive modelling, and statistical analysis. Relevant examples of analytical projects or fraud detection models are welcome.

Turn complex financial data into actionable intelligence that protects customers and prevents fraud.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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