Job Summary:We are seeking a highly skilled and analytical Fraud Modelling Specialist to join our Risk Analytics team. The ideal candidate will have a strong background in data science, with hands-on experience in developing predictive models to detect and prevent fraudulent activities. Proficiency in Python and a deep understanding of statistical modeling techniques are essential for this role.Key Responsibilities:Design, develop, and deploy fraud detection models using machine learning and statistical techniques.Analyze large datasets to identify fraud patterns and trends.Collaborate with cross-functional teams including Risk, Engineering, and Product to implement real-time fraud prevention strategies.Continuously monitor model performance and recalibrate as needed to maintain accuracy and effectiveness.Develop and maintain robust documentation for models, methodologies, and processes.Stay updated with the latest advancements in fraud detection technologies and modeling techniques.Required Qualifications:Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.Proven experience in fraud analytics or risk modeling.Strong programming skills in Python, including libraries such as pandas, scikit-learn, NumPy, and matplotlib.Experience with model development lifecycle: data preprocessing, feature engineering, model training, validation, and deployment.Familiarity with SQL and data visualization tools is a plus.Strong problem-solving skills and attention to detail.Preferred Qualifications:Knowledge of anomaly detection, supervised and unsupervised learning techniques.Exposure to real-time fraud detection systems.