AI led Credit Risk Modeling Senior Consultant

Job Summary We are seeking an experienced Credit Risk Modeller with strong hands-on expertise in credit risk modelling and bureau data analysis. The role involves developing, validating, and maintaining credit risk models to support lending decisions and portfolio risk management. Key Responsibilities Develop, enhance, and maintain credit risk models including application scorecards, behavioral scorecards, and risk segmentation models. Perform data analysis using internal and external bureau data sources. Collaborate with stakeholders to identify business requirements and develop solutions that meet their needs. Provide expert-level guidance on credit risk modelling best practices and methodologies. Stay up-to-date with industry trends and developments in credit risk modelling and apply this knowledge to improve model performance and accuracy. Key Requirements Strong hands-on expertise in credit risk modelling and bureau data analysis. Experience with developing, validating, and maintaining credit risk models including application scorecards, behavioral scorecards, and risk segmentation models. Strong analytical skills with the ability to perform complex data analysis using internal and external bureau data sources. Excellent communication and interpersonal skills with the ability to collaborate effectively with stakeholders. Ability to work independently and as part of a team. Strong problem-solving skills with the ability to identify and resolve complex issues. Experience working in a fast-paced environment with multiple priorities and deadlines. Education Bachelor's degree in a quantitative field such as mathematics, statistics, or computer science. Master's degree in a related field is an asset. Certifications and Training Credit Risk Modelling Certification (CRM) or equivalent is an asset. Strong understanding of credit risk modelling concepts, theories, and methodologies. Familiarity with machine learning algorithms and their applications in credit risk modelling. Experience working with large datasets and performing data analysis using programming languages such as Python, R, or SQL. Benefits Competitive salary and benefits package. Opportunities for professional growth and development. Collaborative and dynamic work environment. Flexible working arrangements including remote work options. Professional development opportunities including training and certification programs.