Fraud Data Scientist

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