Data Analyst with 7+ years of experience, currently based in Washington D.C.
- Developed graph network using networkx and pandas Python packages to determine zip-code eligibility for newly proposed small-business mailing services, enabling revenue opportunities in zip-codes forecasted to increase local package deliveries by 87%.
- Created Random Forest classifier (using scikit-learn) to make predictions regarding zip-codes with missing data, correctly classifying viability in 79% of cases.
- Supported COVID test-kit delivery by building automated Power BI reports, leveraging cloud Azure services, and Power Automate paired with Python code to ingest inventory data and produce real-time analytics regarding optimal operational actions. This analytic solution identifies and resolves supply chain concerns using anomaly detection and simulation.
- Trained k-nearest neighbor model in R to identify existing facilities most likely to have underutilized square footage, exposing a multi-million-dollar revenue opportunity.
- Managed and coached team of 6 Business Analysts and 4 Contractors to develop Hadoop / Hive data models, Qlik visualizations, SQL queries, and machine learning models.
- Used open-cv and trained a Deep Neural Net Computer Vision model to identify real-time utilization of a critical sorting machine component, to alert operations management to divert resources and improve efficiencies.
- Used statistical methods (correlation, ANOVA, feature selection) to test existing reporting metrics for predictive validity and update metrics to enhance leadership decision making.
- Responsible for developing, maintaining, and operating staffing optimization model using Excel Simplex solver, representing over 250 facilities and 60,000 full-time employees. Staffing realignment as a direct result of the model resulted in a workhour reduction of 8% and annual savings in excess of $12 million.
- Earned USPS Lean Six Sigma Green Belt certification, designing a process to minimize truck loading errors and increase schedule adherence, resulting in annual savings of over $250,000 and late trip reduction of 22%.
MS Analytics
- Anticipated graduation date of Sep. 2022
BS Industrial & Systems Engineering
- 4 year member of men’s varsity Swimming and Diving team, earning athletic academic honors
- Professional Internship with Disney Parks & Resorts in Revenue Management & Analytics
- Skills: Python (pandas, numpy, scikit-learn, scipy, networkx, open-cv, matplotlib, jupyter); R (tidyverse, ggplot2, randomForest); Data Visualization and Storytelling (Qlik, Power BI, Tableau); Microsoft Office / Power Platform (Excel, Azure, PowerPoint); SQL
- Interests: Traveling; Swimming & Water Polo; Guitars; Technology; Reading; Music