Job Description: We are looking for Professionals with experience between 3-6 Years in the field of Predictive Modelling with strong foundations in credit Risk, Banking and Finance. Credit Risk Modelling professional will be responsible for developing, validating, and maintaining statistical and machine-learning models used to assess and manage credit risk across different portfolios. The role involves working closely with risk, finance, product, and regulatory teams to ensure models are robust, compliant, and aligned with business strategy.
Responsibilities: Build quantitative scorecards for underwriting, behavioral scoring, and collections.
Implement models using R, Python, SAS, SQL , or equivalent platforms.
Perform feature engineering, variable selection, model calibration, and back-testing.
Conduct regular performance monitoring and benchmarking of models.
Validate internal models as per regulatory guidelines.
Document model assumptions, methodologies, and limitations.
Partner with credit underwriting, collections, finance, stress testing, and product teams.
Qualifications: Bachelor’s or master’s degree in Statistics, Mathematics, Economics, Finance, Engineering, Data Science , or related fields.
3+ years of experience (depending on role level) in credit risk modelling or quantitative analytics.
Proficiency in Python/R/SAS , SQL, and advanced statistical and ML techniques.
Strong understanding of banking credit products (retail or wholesale).
Experience with model development/validation frameworks.
Preferred
Exposure to machine learning (Random Forest, Gradient Boosting, XGBoost).
