Risk Analyst

Job description

Key Responsibilities • Retail Credit Risk Model Management and Validation: o Lead the validation of complex underwriting, collection, and ECL models independently. o Perform comprehensive model performance analysis and drive the investigation of model and portfolio variances. o Ensure that all model validation procedures meet the organization’s risk assessment standards. • Advanced Data Analysis and Reporting: o Oversee the preparation and consolidation of key risk analysis reports and presentations for senior management committees. o Automate and streamline reporting processes to generate actionable insights and drive value across stakeholders. o Ensure the accuracy and relevance of all reports and dashboards, contributing to improved decision-making. • Strategic Risk Insights and Advisory: o Lead the deep-dive investigations into unusual model behaviours and portfolio performance discrepancies, advising the business on necessary actions. o Use advanced analytics to ensure the effective execution of risk analysis and provide strategic insights to the business. • Stakeholder Engagement and Technical Leadership: o Act as a technical lead in collaborating with senior stakeholders to ensure model validation and risk management procedures align with business objectives. o Provide expert guidance to junior team members, ensuring the team adheres to best practices in model validation and risk analytics. • Leadership in Team Development and Culture Building: o Champion the development of a purpose-driven, high-performance culture within the team. o Lead the training and mentoring of junior associates, supporting their professional growth and technical expertise. o Contribute to strategic decision-making, ensuring alignment between credit risk models and business growth. Education Master’s Degree in Statistics, Economics, Mathematics, Engineering; MBA Experience 6 to 9 Years of relevant experience Skills & Competencies • Strong expertise in coding with Python, SQL, and optionally SAS. • Advanced knowledge of MS-Office Suite, with expert skills in data analysis and visualization tools. • In-depth experience in analysing and validating credit risk scorecards and bureau data. • Strong capability in investigating and analysing significant variances in MI and model performance. • Expertise in advanced machine learning models like Gradient Boosting,Neural Networks, Random Forest, etc. is highly preferred. • Strong understanding of Data Warehouse, Cloud Data platforms, and their integration with model validation. • Strong leadership and project management skills, with the ability to influence and guide team members and business stakeholders.