Transforming Data into Actionable Insights
My work applies data analysis, feature engineering, and machine learning to
drive measurable improvements in business decisions.
Explore my projects to see how I turn data into practical solutions. Click any project to learn more.
A robust approach to determine whether improvements are statistically meaningful and
practically relevant.
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Built product classification with PCA for dimensionality reduction and
Fuzzy C-Means clustering. -
Created a strategic 2x2 matrix to guide inventory, forecasting, and marketing decisions.
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Addressed multicollinearity and improved cluster visualization to enhance operational efficiency and profitability.
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Built a dynamic inventory and production system with a flexible TWCV algorithm.
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Used analytics for capacity planning and adaptive inventory adjustments.
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Cut starting inventory by 20%,
reducing stockouts and improving efficiency.
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Built a dynamic system to optimize production during peak demand.
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Used Quantile Transformer and AHP to rank products by capacity, revenue, and backorder risk.
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Improved inventory management by resolving replenishment issues and data anomalies.
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Built Python algorithms to detect errors and optimize transaction records.
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Delivered recommendations for accurate tracking, cancellations, and SKU analysis, boosting data integrity and efficiency.