Data Scientist (Risk Modeling) Executive Monee Credit
Job Description
Job Description
- 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.
- 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
More Info
Key Skills
ensemble methods
scikit-learn
LightGBM
random forests
gradient boosting
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