Fraud Analytics || Mumbai || WFO

About the role

Engineer high-impact features from structured and alternate data sources. Address challenges such as class imbalance, data drift, and evolving fraud typologies. 3-6 years of experience in Fraud Analytics, Risk Modeling, Fintech, or Banking. Generous holiday leave policy. Opportunity to work in a reputed financial services organization in Mumbai.

What you'll do

• Analyze large-scale transactional and behavioral datasets to identify fraud patterns and risk signals
• Design, develop, and optimize ML models for: Fraud detection (classification), Anomaly detection (unsupervised/semi-supervised), Risk scoring systems
• Define model evaluation frameworks
• Develop scalable training pipelines and collaborate on production deployment (batch & real-time)
• Implement model monitoring, retraining, and explainability (e.g., SHAP-based analysis)

What you need

• 3–6 yrs of experience
• Analytics
• Statistics
• Machine learning
• Python
• Pandas
• NumPy
• Any graduate

Good to have

• Scikit-learn
• TensorFlow
• PyTorch