The Data Analyst is responsible for collecting and analysing relevant data from a wide variety of sources to provide practical and meaningful data insight reports, which guide credit risk decision making and general management actions. He/she will support operational data analytics & insights, credit scoring and management reporting.
- Sourcing data from various sources including SQL databases and CSV files.
- Transforming and automating repetitive data tasks.
- Data modelling & data visualization to evaluate performance and trends, using interactive visuals and dashboards.
- Statistical and predictive analysis to model uncertain scenarios.
- Credit Risk Scoring and segmentation to facilitate credit risk-based decision making
- Developing processes and procedures for integrating Credit scoring and risk-based pricing models into underwriting operations.
- Training of Staff (Branches & Head Office) regarding Credit Risk Scoring processes and outcomes.
- Providing solutions for queries from Branches and Head Office departments for Business and Data Insights Management Reporting.
- Creating and maintaining regular and ad-hoc business operational reports, key risk indicators, among others.
- Collecting credit risk related data and conducting analysis, segmentation, trending, forecasting and interpretation of risk management issues and concerns relevant to a portfolio of loan products using statistical techniques.
- Supporting credit portfolio stress testing and scenario development.
- Creating analytical datasets by performing exhaustive descriptive analysis, data cleansing and normalization, and investigation of business rules that create the data.
- Developing systems and processes for gathering and storing data for future work and projects.
- Developing new, improving current and automating processes and reports routinely utilized using statistical and data science techniques.
- Validating IFRS9 Modelling Variables, Assumptions, MDQs and ECL outputs for accurate Loan Loss Provisions.
To perform the job successfully, an individual should demonstrate the following competencies:
- Vintage Analysis Modelling.
- Credit Portfolio Stress Testing Modelling.
- Marketing Intelligence Analytics.
- Technical Understanding R programming and SQL.
- Experience with Visualization Tools: Power Bi; Tableau, etc.
- Machine learning concepts to constantly improve automated decision making.
- Regression Analysis – Fundamentals & Practical Applications.
- Statistical and predictive analysis.
- Data transformation, modeling, and visualization.
- Well-developed inter-personal and communication skills
- Proactive and logical approach with attention to detail.
- Capable of performing under pressure and within time constraints.
- Self-motivated and ability to work effectively with less supervision
- Minimum Honors University degree in Statistics, Applied Mathematics, Economics / Econometrics, Actuarial Science, Computer Science, Information Technology, Operations Research, industrial Engineering or other quantitative disciplines.
- 3 Years Experience as a Data Analyst, Business Intelligence Analyst, Data Visualization Specialist, Quantitative Analyst, or Data Scientist.
- Any experience within Micro Finance / Credit Risk / Banking / Mobile Networks is an added advantage
