C1 - Credit Risk Modeler

EXL Talent Acquisition Team; Gurugram District; On-site; INR 800,000 - 1,400,000; Full time

Job summary

EXL Talent Acquisition Team is seeking a data-focused professional to design and build credit risk scorecards for creditworthiness and collections optimization. You will extract and preprocess data from diverse sources using SQL and develop ML models in Python (pandas, scikit-learn) for collections performance and delinquency prediction.

You will monitor model performance, perform backtesting and recalibration, and ensure compliance with regulatory standards.

Qualifications

• Experience designing credit risk scorecards (application, behavioral, collections).
• Extracting, cleaning, and preprocessing data from multiple sources using SQL.
• Developing ML models for collections performance and delinquency with Python (pandas, scikit-learn).
• Ability to validate models, backtest, recalibrate, and document assumptions for governance.

Responsibilities

• Design and build credit risk scorecards to predict creditworthiness.
• Extract and preprocess data from various sources using SQL.
• Develop ML models for collections performance and delinquency with Python.
• Monitor model performance, backtest, recalibrate, and validate per regulatory standards.
• Collaborate with business and data teams to translate requirements into modeling specs.
• Document modeling processes, assumptions, and results for governance and audits.

Skills

SQL

Python

Pandas

scikit-learn

Tools

Backtesting

Job description

Design and build credit risk scorecards (application, behavioral, and collections scorecards) to predict creditworthiness and optimize account management strategies.

Extract, clean, and preprocess data from various sources using SQL.

Develop and implement machine learning models for collections performance and delinquency prediction using Python (including libraries like pandas, scikit-learn).

Monitor model performance, conduct backtesting, recalibration, and validation adhering to regulatory standards.

Collaborate with business and data teams to translate credit risk requirements into modeling specifications.

Document modeling processes, assumptions, and results for internal governance and audit purposes.