The Concept Group is a holding company for companies established in 1992. Subsidiaries under the Group include: Rosabon Financial Services - Nigeria’s Leading Financial Intermediary and Equipment Leasing Company, Concept Nova - Bespoke Enterprise IT Solutions Company,Percy Aitkins - Bureau De Change.
We are recruiting to fill the position below:
Job Title: Junior Quant / Scorecard Analyst
Location: Yaba, Lagos
Employment Type: Full-time
Job Purpose
- The Junior Quant / Scorecard Analyst supports the development, monitoring, and maintenance of credit scoring models and quantitative risk tools.
- The role focuses on data preparation, modelling assistance, portfolio analytics, and documentation to enhance credit decision-making and improve portfolio performance across retail, SME, MFB lending, and fintech lending products.
Key Responsibilities
Data Preparation & Management:
- Extract, clean, and organize datasets for credit modelling and analysis.
- Work with data engineering and MIS teams to ensure data integrity and completeness.
- Conduct data quality checks and produce summary statistics.
Scorecard & Model Development Support:
- Assist seniors in building credit scoring models (application, behavior, collection).
- Perform exploratory data analysis (EDA) and variable selection.
- Support model development using logistic regression, decision trees, and basic ML techniques.
- Prepare model datasets, feature engineering, and transformations.
Model Monitoring & Performance Tracking:
- Monitor model KPIs such as Gini, KS, AUC, PSI, and score distribution.
- Track override patterns, approval rates, and model drift.
- Prepare monthly and quarterly model performance reports.
Portfolio Analytics:
- Assist with analysis of delinquency trends, roll rates, NPL ratios, and credit losses.
- Support cohort/vintage analysis for MFB and money lending products.
- Provide insights to help refine underwriting policies and risk strategies.
IFRS 9 & Regulatory Support (Basic):
- Support model documentation and basic calculations for expected credit loss (ECL).
- Assist with regulatory submissions related to credit scoring or risk models.
- Maintain compliance with data and modelling standards.
Documentation & Reporting:
- Prepare model documentation (methodology, testing, assumptions).
- Draft monitoring reports and dashboards for internal users.
- Ensure all development steps follow model governance rules.
Collaboration:
- Work with underwriters, credit analysts, and product teams to understand business requirements.
- Provide quantitative insights for new product development and risk appetite changes.
- Support Senior Modellers and Analysts in project execution.
Key Performance Indicators (KPIs)
Model Development & Support:
- Accuracy and timeliness of data preparation for modelling.
- Contribution to scorecard development (quality of EDA, feature selection, model testing).
- Reduction in model development timelines.
Model Performance Monitoring:
- Timely submission of monthly/quarterly monitoring reports.
- Accuracy of model KPIs (AUC/Gini/KS/PSI) tracking.
- Early identification of model drift or performance issues.
Data Quality & Governance:
- Reduction in errors in modelling datasets.
- Compliance with data governance and documentation standards.
- Number of data quality issues detected and resolved.
Portfolio Impact:
- Improvements in approval rate or bad rate linked to scorecard refinements.
- Accuracy of risk segmentation insights.
- Effectiveness of analytical support for credit policy changes.
Efficiency & Automation:
- Number of automated scripts/reports developed (e.g., Python, SQL).
- Reduction in manual reporting effort.
- Improvement in turnaround time for analytical tasks.
Collaboration & Stakeholder Support:
- Feedback from senior modellers, underwriters, and product teams.
- Timeliness and quality of ad-hoc analysis delivered.
- Contribution to cross-functional risk initiatives.
Qualifications & Experience
- Bachelor’s Degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Engineering, or similar.
- 1 - 3 years of experience in credit analytics, data analysis, quantitative modelling, or related fields.
- Knowledge of Python, R, or SAS (basic to intermediate).
- Ability to write SQL queries and work with structured datasets.
- Understanding of credit scoring, logistic regression, and model validation concepts.
- Experience in banking, microfinance, or digital lending is an advantage.
Skills & Competencies:
- Strong quantitative and analytical skills.
- Basic knowledge of credit risk metrics and scorecard frameworks.
- Proficiency in Python/R and SQL for modelling and analysis.
- Ability to work with large datasets and identify patterns.
- Good communication and documentation skills.
- Willingness to learn advanced modelling and machine learning techniques.
- Detail-oriented and committed to data accuracy.