Supply Chain &

Data Analytics

Portfolio

Supply chain analyst with 5 years of experience supporting data operations and supply chain logistics for municipal, federal, and international government programs. Delivered data systems and analytic insights for health product logistics in 24 countries across Africa, which supported stockout/expiry prevention strategies that ultimately saved the lives of over 20k HIV patients while also saving $1.5million in tax-payer funds over 5 years.

Passionate about resolving supply chain bottlenecks and preventing stockouts. Relied on for translating technical analysis into useful insights across teams.

Supply Chain Projects

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Demand Forecast Planning

Computing demand forecasts for fast-food ingredients.

Objective: anticipate demand for ingredients that will be needed next year.

Method: ARIMA and Holt-Winters models

Result: 75% increase in accuracy with revised seasonality models.

Role: School Project

Skills: Python, scikit-learn, statsmodels

Regional Inventory Data Reporting

First local-level visibility into inventory data for HIV products.

Objective: to display latest inventory levels at all 3k+ pharmacies and last-mile distribution warehouses across Zambia.

Method: ETL Pipeline with reported inventory data (excel) to arcGIS.

Result: new access into local inventory levels for supply chain teams.

Role: Project Lead, USAID Global Health Supply Chain

Skills: Python, Esri Arcade

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Sourcing & Production Strategy

Supply chain analysis and strategy for winter sport textiles.

Objective: broad goal of creating recommendations based on analysis.

Method: Newsvendor model.

Result: identified new suppliers and production strategy.

Role: School Project

Skills: AMPL

Marine Safety Incident Tracking

Live data map with shipping incidents in strategic locations.

Objective: provide historical and live data of globally reported maritime incidents, categorized by type of event.

Method: Live AIS data fed in to preset cartographic templates.

Result: Historical and live tracking of reported maritime incidents categorized by type.

Role: School Project

Skills: arcGIS

Machine Learning Projects

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Wine Quality Prediction

Machine learning model to predict the quality of wine samples.

Objective: correctly predict the quality of Portuguese wine based on the physical and chemical characteristics of a sample.

Method: K-Nearest Neighbor classifier model.

Result: 80% accuracy in predicting high quality wines.

Role: School Project

Skills: Python, scikit-learn

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Risk Analysis for Mortgage Arrears

Predicting risk for mortgage payment defaults.

Objective: detect tenants at most likely to default on their mortgage payments based on past payments.

Method: K-Nearest Neighbor, Random Forest, and Logistic Regression models.

Result: 77% accuracy for medium-risk defaults, and 58% accuracy for high-risk defaults.

Role: School Project

Skills: Python, scikit-learn

Econometric Research

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Political Risk and Microeconomic Development

Measuring the microeconomic impact of political instability on tourism enterprise growth.

Objective: detect tenants most likely to default on their mortgage payments based on past payments.

Method: multivariate regression model.

Result: statistically significant results showing the Sub-Saharan tourism industry faced 2% slower growth than other industries in volatile political climates.

Role: School Paper

Skills: Stata