Fraud Data Scientist

Key Responsibilities:Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activityUtilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including first-party and third-party fraud).Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures.Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies.Technical Skills Needed:3+ years of experience in Python coding, SQL, Machine LearningHands-on experience with XGBoost, Random Forest, Experience in end-to-end ML model development: Build and deploy ML models for fraud detection.Analyze large datasets to identify fraud patterns and anomalies.Collaborate with cross-functional teams to enhance fraud prevention strategies.Good understanding of: Imbalanced data handling Model evaluation metrics Model explain ability Exposure to LLMs/RAG concepts BFSI domain is good to have