Fraud Detection ML Engineer

Job Description Roles & Responsibilities Fraud Detection ML Engineer Experience: 4–8 years Job Summary: Develop machine-learning models to identify fraudulent transactions and suspicious financial activities. Key Responsibilities: Develop fraud detection and anomaly detection models. Analyze transaction and customer behaviour. Build real-time fraud scoring systems. Work with data engineering teams to process high-volume transaction data. Monitor model performance and false-positive rates. Develop predictive models for emerging fraud patterns. Desired Candidate Profile Mandatory Skills: Python, Machine Learning, SQL, Pandas, Scikit-learn Good to Have: PySpark, Kafka, real-time analytics, fraud/AML experience. Employment Type Full-time Company Industry RecruitmentPlacement FirmExecutive Search Department / Functional Area Software DevelopmentApplication Development (IT Software) Keywords Machine Learning EngineerFraudSenior ML EngineerRisk Management Get real-time job updates only on our App