Data Scientist (Risk Modeling) Executive Monee Credit

• Develop and maintain MIS reports to monitor key portfolio performance and advise management on risk profiles.
• Analyse portfolio performance, identify trends & drivers, draw insights and optimize the underwriting policies Credit
• Design and implement champion challenger mechanism to optimise the underwriting.
• Participate in credit portfolio stress testing on a regular basis to fulfill both internal and regulatory requirements.
• Lead delivery of credit risk system projects and/or tactical system changes.
• Administer credit rules, scorecards, limit assignments in retail and SME credit underwriting system(s), including the following: Administer risk data mart and conduct associated problem-solving.
• Communicate issues/improvements relating to credit risk systems and data inputs/outputs, and act as primary liaison for vendor engagement, vendor management and onboarding.
• Work closely with business team, dev, and other functions as necessary.

Requirements

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field
• min 2 years of hands-on experience in statistical modeling, machine learning, data science, or credit risk analytics roles
• Strong proficiency in SQL — ability to write complex queries, perform data exploration, and build ETL logic for modeling datasets
• Strong proficiency in Python — pandas, scikit-learn, and related ML libraries for model training and evaluation
• Solid understanding of traditional ML methods: logistic regression, gradient boosting (XGBoost, LightGBM), random forests, ensemble methods
• Fluent in english