DEADLINE: 12/05/2025

Data Analyst

Full-time

Finca is hiring a Data Analyst is responsible for collecting and analyzing 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.

Department: Data Analytics and Credit Risk Management

Main Duties and Responsibilities

Sourcing data from various sources including SQL databases and CSV files.
Transforming and automating repetitive data tasks.
Data modeling & 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.

Competencies

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 of 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 interpersonal 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.

Qualifications, Skills, and Experience

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 Microfinance, Credit Risk, Banking, or Mobile Networks is an added advantage.

How to Apply

All candidates who wish to take up this role in the aforementioned capacity are encouraged to send their applications with the following documents: