Lead, Credit Modeller & Data Scientist

Job Summary

We are seeking an experienced Lead, Credit Modeller & Data Scientist to drive the development and optimization of credit risk models and data-driven decision systems. This role will play a critical part in enhancing credit underwriting, portfolio performance, and risk analytics using advanced statistical and machine learning techniques.

Key Responsibilities

Credit Risk Modelling

• Develop and manage credit scoring models (application, behavioral, and collections).
• Build PD, LGD, and EAD models in line with IFRS 9 requirements.
• Conduct portfolio analysis, forecasting, and risk segmentation.

Machine Learning & Analytics

• Design and deploy predictive models (e.g., fraud detection, churn, collections).
• Apply machine learning techniques to improve decision-making and reduce risk exposure.

Model Validation & Monitoring

• Track model performance using key metrics (AUC, Gini, KS, ROC).
• Perform regular back-testing, validation, and recalibration.

Data & Infrastructure

• Ensure data quality, consistency, and governance standards.
• Collaborate with data engineering teams to build scalable pipelines.

Portfolio & Strategy

• Analyze portfolio trends (NPLs, ECL, roll rates).
• Support credit policy and risk strategy with data insights.

Automation & Decision Systems

• Integrate models into automated credit decision engines.
• Support digital lending and real-time risk assessment.

Leadership

• Lead and mentor a team of analysts and data scientists.
• Present insights to senior stakeholders and regulators.

Requirements

• Bachelor’s or Master’s degree in a quantitative field (Statistics, Mathematics, Data Science, Finance, etc.)
• 5–10+ years of experience in credit risk modelling or data science
• Strong knowledge of IFRS 9, Basel frameworks, and credit risk analytics
• Proficiency in Python, R, SQL, or SAS
• Experience with BI tools (Power BI, Tableau)
• Strong leadership and stakeholder management skills

How to Apply

Interested and qualified candidates should apply via Indeed with an updated CV.

Work Location

Hybrid remote in Yaba