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We are looking for a hands-on Data Scientist / ML Engineer to build and deploy credit risk and decisioning models for an NBFC/banking workplace. The role focuses on production-grade machine learning systems, including model development, deployment, scalability, and integration into decision engines. This is not a research-heavy AI role-the expectation is solid ownership of end-to-end pipelines, from data to production, with emphasis on robustness, performance, and business impact. Key Responsibilities: Credit Risk & Decisioning Models Develop and maintain models for: Credit risk (PD, delinquency, segmentation) Customer behaviour (collections, engagement, response) Income estimation / surrogate modelling (where applicable) Work with bureau data (e.g., CIBIL/CRIF), transactional data, and alternative data sources Translate business policies into model-driven decision frameworks Data Engineering & Feature Pipelines Build scalable feature pipelines using: Python / PySpark / SQL Handle large-scale datasets (structured + semi-structured) Implement robust feature engineering (e.g., bureau features, exposure, EMI, leverage, etc.) Model Deployment & Integration Deploy models into production systems using: Docker, Kubernetes, or similar containerization tools Integrate models with decision engines / APIs Ensure low-latency and high-throughput inference pipelines MLOps, Testing & Monitoring Implement: Integration testing for model pipelines Stress testing (performance under load) Model monitoring (drift, stability, performance) Work with DevOps teams to ensure reliable production systems Handle versioning, rollback strategies, and model lifecycle management Cloud & Infrastructure Work on AWS-based settings (or equivalent cloud platforms) Understand distributed systems and compute optimization Optimize pipelines for performance and cost Cross-functional Collaboration Work closely with: Risk teams Product / business stakeholders Data engineering & platform teams Translate business requirements into scalable technical solutions Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .