Role Overview: The incumbent will play a critical role in leveraging data analytics to assess, identify, and mitigate risks. This role is pivotal in developing and implementing risk models and early warning signals to safeguard portfolio health and enhance decision-making. Key Responsibilities: 1. Conduct comprehensive credit risk assessments and implement mitigation strategies. 2. Develop and deploy risk models tailored to organizational needs. 3. Implement and monitor Early Warning Signals (EWS) for proactive risk management. 4. Own and manage model validation, portfolio risk metrics, and EWS performance metrics. Key Skills & Competencies: - Proficiency in SQL, Python/R for data analysis and model development. - Expertise in data manipulation/statistics. - In-depth knowledge of credit risk concepts and frameworks. - Candidates from similar roles in organizations specializing in risk management, financial services, or analytics-driven functions. Profile Requirements: Education: - Minimum: Graduation or Master's degree. - Preferred: Graduation/Master's with Statistics as one of the subjects. Experience: - Required: 3-5 years of hands-on experience in data analysis and risk modeling. - Preferred: Exposure to dimensionality reduction, regularization techniques, and feature selection.