Shaiful Islam

• Processed and modeled 25-year longitudinal panel datasets (2000–2024) across 14 G7 and ASEAN economies using World Bank and ILOSTAT data to evaluate structural labor market changes.
• Applied advanced econometric diagnostics in Gretl and EViews, utilizing IPS unit root and Pedroni cointegration tests to ensure data stationarity and optimal model selection.
• Developed Random Effects regression models with Arellano cluster-robust standard errors, quantifying that urbanization reduces vulnerable employment more effectively in G7 (-0.353) than in ASEAN (-0.237) markets.

• Analyzed a Kaggle credit risk dataset using Python to predict bank loan defaults
• Evaluated six classification models, identifying Random Forest as the optimal algorithm for balancing precision and recall in default prediction.
• Performed data preprocessing, feature engineering, and model evaluation using Scikit-learn and Pandas
• Visualized model performance metrics and compared predictive accuracy across all classifiers.

• Excel Data Analytics: Automated KPI tracking and sales trend reporting.

• Consolidated 18 months of sales data using XLOOKUP and INDEX MATCH to streamline manual

data reconciliation. Applied logical functions and custom formatting to normalize business metrics

• Designed dynamic dashboards to track regional KPIs, enabling stakeholders to identify

underperforming sales territories in real-time. Implemented Timelines and Slicers for interactive multi-dimensional analysis