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.

Valuable understanding of:
Imbalanced data handling
Model evaluation metrics
Model explain ability
Exposure to LLMs/RAG concepts
BFSI domain is valuable to have

📌 Fraud Data Scientist Bengaluru
🏢 Straive
📍 Bengaluru