Role: Financial Credit Risk Modeler
Work Mode: Hybrid (4 days WFO)
Location: Chennai (GBS)
Experience: 4+ years
Client: One Magnify/Ford

Notice Period: Immediate to 30 days About the Role

We are seeking a hands-on Financial Credit Risk Modeler to develop and/or validate credit risk models end to end. This is a core modeling role—implementation-only or reporting-centric experience will not qualify.

Key Responsibilities
Develop and validate credit risk models with no trade-offs on rigor and compliance.
Build end-to-end scorecards using logistic regression, including data preparation, variable selection, model training, calibration, stability/monitoring, and documentation.
Design and/or validate IFRS 9 models such as PD, LGD (and where applicable EAD), including segmentation, model methodology, backtesting, and governance artifacts.
Execute predictive modeling using statistical techniques such as regression and time series for credit risk use cases.
Produce comprehensive model documentation: development reports, validation reports, performance monitoring, and remediation plans.
Partner with stakeholders (risk, data, business, audit) to align methods and ensure model risk management standards are met.
Must-Have Qualifications
Minimum 3+ years of hands-on experience in either:




Model Development, or
Model Validation (Note: Implementation-only or reporting-focused work does not count toward the requirement.)
Proven experience with credit risk models:
Scorecard development using logistic regression (end to end, not limited to data cleansing/EDA).
IFRS 9 models (PD, LGD) and/or other predictive models using time series/regression.
Solid understanding of statistical modeling concepts: sampling, WoE/IV, feature engineering, multicollinearity checks, calibration, discrimination/KS/AUC, stability/PSI, and backtesting.
AI/ML Exposure
Basic working knowledge of AI/ML concepts and practical exposure in current/previous roles (e.g., LLMs, AutoML, GCP-native ML services). Curiosity and willingness to learn are essential.
Tools and Technology
Preferred: SAS and Google Cloud Platform (GCP).
Open to solid candidates with modeling experience in Python or R and readiness to ramp on SAS/GCP.
Nice to Have
Experience with MRM frameworks and regulatory expectations (IFRS 9 governance, model risk policies).
Familiarity with challenger models, reject inference, and scorecard overlays.
Exposure to MLOps/Model monitoring on cloud platforms.

📌 Financial Credit Risk Modeler (Chennai)
🏢 Bsri Solutions
📍 Chennai