• Led business intelligence projects, managing multiple direct reports; responsible for project oversight and strategy, task delegation, and final deliverables
• Developed a database and application that managed the annual quoting of $26,000,000, reduced the time spent creating quotes by 66%, and allowed tracking of quoting KPIs
• Managed the planning, design, and implementation of a maintenance inventory system that resulted in a projected decrease of on hand maintenance inventory by 40%, reduced administrative hours spent managing inventory by 87%, and reduced part outages by 80%
• Executed and expanded reoccurring database hygiene processes using SQL
• Created dashboards in PowerBi for the directors of the sales and operations department, allowing continual monitoring of departmental KPIs and progress towards strategic departmental objectives
• Developed machine learning algorithms using R to predict potential candidates tenures
• Increased employee engagement by serving as the president of the activates committee and expanded safety protocols by serving as a member of the safety committee
• Assisted in the facilitation of a Business Intelligence and Analytics course, providing support to students in understanding complex concepts and analysis tools related to data analysis for business decision-making
• Contributed to students' comprehension of data analytics by holding office hours on topics such as relational data bases, data sourcing, data cleaning and manipulation, data modeling, data visualization, and strategic decision making
Woked cross functionally with both the credit and risk teams.
• Analyzed default records of lessee to determine the accuracy of predictive analytic tools at rank ordering the risk of borrows, presented to executives a recommendation to change predictive analytic tools
• Managed the annual review of lessee’s financial statements and leased assets to determine the creditworthiness of borrowers in possession of $20,000,000 of company assets
• Executed annual loss given default analysis to determine the cumulative expected losses on all outstanding loans within the leasing portfolio
