Job Description

Requirements

• Bachelor's degree in finance, Economics, Data Science, Statistics, Business, Operational research or a related field.
• Master's degree in a relevant field or professional certifications is a plus
• 3-5 years of experience in credit risk collections management, preferably within the SME sector
• Proven track record of improving collections outcomes and operational efficiencies
• Experience with collections and recovery strategies is essential
• Hands-on experience in data analytics, statistical modelling, and risk scoring
• Proficiency in data analysis tools (e.g., SQL, R, Python)
• Experience with data visualization tools (e.g., Tableau, Power BI)
• Strong Excel skills for financial modeling and analysis
• In-depth knowledge of credit bureau data, scoring methods, and financial regulations related to collections

• Conduct a thorough analysis of the SME portfolio to identify potential risks and trends
• Develop and implement collection strategies based on data-driven insights to minimize delinquency and improve recovery rates
• Monitor execution and performance of strategies and ensure that strategies are amended and kept up to date
• Develop and maintain predictive models for collections to identify early warning signs and take preventative measures
• Regularly monitor the SME portfolio performance, identifying risk triggers, delinquency trends, and opportunities for improvement
• Provide actionable insights and recommendations to the Data Science and Operational Collections teams to mitigate risks
• Develop and maintain dashboards and reports to track key performance metrics (KPIs), delinquency, and recovery rates
• Analyse large datasets using statistical methods to inform credit risk and collections strategies
• Collaborate with the Data Science Manager to improve the accuracy and predictive power of credit risk models
• Support the Collections team by providing data-driven insights for operational decision-making

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