- Extract, clean, and preprocess financial datasets for model development.

- Perform exploratory data analysis (EDA) to identify trends and variable relationships.

- Define bad definition, observation, and performance windows.

- Develop PD, LGD, and EAD models as per Basel III / IFRS9 guidelines.

- Build Application, Behavioral, and Collection scorecards for retail/wholesale portfolios.

- Apply statistical and machine learning techniques (Logistic Regression, Decision Trees, Random Forest, etc.).

- Conduct variable selection, transformation, and feature engineering.

- Evaluate model performance using KS, Gini, AUC, calibration, and stability tests.

- Perform out-of-sample and out-of-time validations.

- Document model methodology, assumptions, and development process.

- Ensure compliance with Basel, IFRS9, CCAR, and internal MRM frameworks.

- Support regulatory reviews, internal audit, and model validation queries.

- Implement model monitoring and recalibration processes.

- Track portfolio drift, PSI, and model performance metrics.

- Conduct root cause analysis for threshold breaches or degradation.

- Automate model monitoring and reporting dashboards using Python, SAS, or SQL.

- Prepare technical documentation and presentations for senior management.

- Collaborate with business, risk, data, and IT teams for model deployment.

- Maintain model inventory, change logs, and governance documentation.

- Stay updated on regulatory and quantitative modeling best practices.

Preferred candidate profile:

- 3 years of experience in credit risk modeling, scorecard development, or risk analytics within banking or BFSI.

- Strong understanding of Basel II/III, IFRS9, CCAR, and CECL regulatory frameworks.

- Proven experience in developing PD, LGD, and EAD models for retail and wholesale portfolios.

- Hands-on proficiency in SAS, Python, SQL, and advanced statistical modeling techniques.

- Solid knowledge of statistical and machine learning methods (Logistic Regression, Decision Trees, Random Forests, etc.).

- Experience in model documentation, validation support, and model performance monitoring.

- Familiarity with model governance, MRM standards (SR 11-7, ECB TRIM), and audit processes.

- Exposure to IFRS9 impairment modeling and portfolio analytics (vintage, roll-rate, delinquency analysis).

- Strong quantitative and analytical skills with background in Statistics, Mathematics, Economics, or Quantitative Finance.

- Excellent communication and presentation abilities for stakeholder engagement.

- Certifications such as FRM, PRM, or CFA preferred.

- Experience working with global banking clients or in a regulatory-driven environment is highly

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Last Active: 10 November 2025

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Applications: 66

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