Credit Score Analyst | Data Analyst | Statistician

Build and maintain behavioural and application credit scorecards, risk-based pricing models, and NPL forecasting models for the Lending Risk Department. Support data-driven lending decisions for retail and SME customers by assessing creditworthiness at origination and throughout the loan lifecycle.

Led end-to-end development of a behavioural scorecard using customer transaction data. Engineered more than 150 behavioural variables across 1-, 3-, and 6-month windows, selected 10 final variables using WoE and IV analysis, and developed a logistic regression scorecard with a base score of 669 and PDO of 20. The model achieved AUC 0.78, KS 0.46, and Gini 0.55 and supports risk-based digital lending limits.

Develop NPL forecasting models for SME and total loan-book portfolios, track NPL, PAR 30/60/90, credit losses, utilisation, and borrower trends, and support risk-based pricing analysis. Designed a monitoring and governance framework for scorecard performance, model stability, and portfolio trends, while preparing methodology documentation and executive presentations for Risk, Analytics, IT, and Business stakeholders.

Performed profitability analysis across vegetables, imported fruits, local fruits, and herbs by evaluating sales volumes, revenue, wastage, and margins. Identified products that drove profitability and those contributing to losses.

Analysed demand patterns and seasonality to inform purchasing and inventory decisions. Compiled, cleaned, and validated operational data, then produced statistical summaries, tables, and charts to support planning, monitoring, resource allocation, and management decision-making.

Built a predictive sales forecasting model that improved forecasting accuracy and provided clients with a more reliable foundation for sales planning. Worked with client teams to convert business needs into measurable analytical requirements and KPIs.

Created an automated real-time Power BI dashboard for management reporting on sales performance, customer retention, and operational efficiency. Audited, cleaned, and consolidated client data to improve reporting reliability and decision quality.

Validated and analysed survey data using CSPro, SPSS, and Excel while following Kenya National Bureau of Statistics data-management protocols. Conducted consistency checks to support accurate and reliable survey datasets.

Updated and maintained the NASSEP V sample frame, clusters, and database; reviewed field data and cluster files; and supported data entry for Post-Enumeration Survey forms. Participated in field data collection for the Kenya Demographic and Health Survey 2022 and the Economic Survey 2022.

Completed a Bachelor of Science in Statistics, developing foundations in statistical analysis, regression, forecasting, survey methodology, sampling, and data analysis.

Completed professional training in data analytics.

Completed training in data analysis, data modelling, and data visualization.