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.

📌 Data Scientist Analytics Coe New Delhi (India)
🏢 Hero FinCorp
📍 India