Portfolio
Selected projects focused on BI, analytics and decision support. Each project includes objective, tech stack and highlights.
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SPY ROI ML Model
Objective: Machine learning model to estimate the probability that the S&P 500 Index will achieve a 6-month forward return greater than +5%. The project includes full feature engineering, model training, evaluation, interpretation, and reproducibility steps.
PythonPandasScikit-learn
- Feature engineering on historical market data
- Evaluation across multiple horizons
- Clear interpretation of results for decision-making
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Dynamic Pricing & Quoting Tool (Excel + VBA)
Objective: BOM-driven costing + bundles + guardrails + PDF/Excel export for a furniture manufacturer.
Advanced ExcelVBA CodePower QueryMacros
- Designed a relational model: Parts → Products (BOM) → Bundles → Price List
- Built quote workflow with validations (no decimals, no zero-price, no empty bundles)
- Implemented UI hierarchy (top-level vs child lines) to prevent pricing confusion
- Exported print-ready PDF (1 page wide) + clean Excel (.xlsx values-only)
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Telecom Churn ML
Objective: Predict churn and identify key drivers to support retention strategies.
PythonPandasScikit-learn
- EDA and data cleaning workflow
- Model comparison using standard metrics
- Insights on key churn drivers
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Happy Insurance BI
Objective: Build BI dashboards for KPIs, trends and operational visibility.
Power BIDAXData Modeling
- Star schema modeling and KPI drilldowns
- Clean dashboard layout with narrative insights
- Focus on stakeholder usability and clarity