A fast-growing fintech company is looking for aQuantitative Analystwith a strong background incredit risk modellingto join its Data & Analytics team. The business provides innovative financial services including mobile money remittances and micro-lending targeting underserved and emerging markets. This is a high-impact midsenior level role for someone who thrives in a fast-paced data-driven environment and is passionate about building robust models that support inclusive lending.
Key Responsibilities
Design build and validatecredit scoring modelsto support decisioning for acquisition behavioural and collections strategies.
Leverage customer data and alternative data sources to improve credit risk assessments and portfolio quality.
Work closely with Risk Product and Finance teams to support strategy around lending pricing and risk appetite.
Monitor model performance and recalibrate as needed to ensure stability and regulatory alignment.
Develop portfolio segmentation strategies and contribute to policy design for credit and collections.
Build dashboards and automated tools to track credit KPIs and risk indicators.
Present insights and model outcomes clearly to business and technical stakeholders.
Requirements
Bachelors or Honours degree in a quantitative discipline (e.g. Statistics Mathematics Actuarial Science Data Science Engineering or Computer Science).
36 years of experiencein a quantitative risk or analytics role with a strong focus oncredit modelling.
Hands-on experience developing validating and deployingcredit risk models(application and behavioural).
Knowledge of credit risk metrics such as PD LGD and EAD.
Strong skills inPythonorR andSQLfor data analysis and modelling.
Solid grasp of statistical and machine learning techniques such as logistic regression decision trees and segmentation.
Strong communication skills with the ability to explain analytical results to non-technical teams.
Nice to Have
Experience usingalternative datain risk modelling particularly in emerging markets.
Exposure to digital lending mobile money or informal credit markets.
Familiarity with Power BI Tableau or other data visualization tools.
Experience working in a cloud environment (AWS GCP Azure).
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