Fraud Data Scientist

Job description

**Key Responsibilities:** - Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity - Utilize 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 Learning - Hands-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