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 valuable to have

📌 Fraud Data Scientist (Bengaluru)
🏢 Straive
📍 Bengaluru