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Jun. 2017Nov. 2017

Advanced Data Analyst

  • Built Machine Learning models such as Logistic Regression, KNN, SVM, Decision Tree, and Gaussian Naive Bayes to create a predictive model that can be utilized to forecast a driver’s likelihood to cause an auto accident. This goal of this effort is to begin to create a suite of predictive analytics that can be commoditized within SambaSafety’s current Risk Management Solution.
    • In order to create the model, I extracted over 200 features from original data stored in MongoDB and selected main features that may affect drivers’ accident risk with pandas and NumPy.
  • Created the ability for SambaSafety to provide customer and channel-partner reporting by conducting exploratory data analysis, data transformation, and data visualization of motor vehicle records data with Tableau.
  • Developed and improved pre-sales models utilizing Python that were utilized to demonstrate the achieved and predicted results of utilizing the software, which resulted in the wins of two of the company’s largest 2017 deals.
Jul. 2017Nov. 2017

Data Analysis Intern

SANS Institute
  • Optimized and automated the scheduling of thousands of instructors to quarterly courses to eliminate manual processes while improving course enrollment.
  • Utilizing Python Gurobi, I developed and applied a mathematical optimization model to solve the problem of matching thousands of instructors’ availability, skills and previous course evaluation results to the appropriate courses for the quarter.
  • The model has enabled SANS Institute to eliminate manual scheduling saving them time and resources, while improving profits by ensuring the best instructor for the course was assigned based on multiple critical factors, including their previous student’s evaluation of the course. Given the success of the current iteration of the model, I have been asked to incorporate more factors such as instructor travel time and site location preference.
Dec. 2015Jun. 2016

Business Intelligence Intern

Comedy Works
  • Improved daily financial reporting process by setting up an interactive Excel Dashboard (VBA) to automatically calculate key components of the financial statements.
  • Increased the 2016 fiscal year budget precision by analyzing the past data and trends using the V-Lookups, Pivot Table and Regression Analysis with Microsoft Excel.
  • Analyzed customer’s payment preferences utilizing Tableau in order to create optimized B2C marketing campaigns and promotions, which helped increase ticket sales.


University of Denver                                                                          

Master of Business Analytics( 3.5 GPA)                                              Sep. 2016 - Nov. 2017

Master of Business Administration(3.44 GPA)                                  Mar. 2014 - Nov. 2017


Data Analyst Nanodegree                                                                      Jun. 2017 - Nov. 2017

Machine Learning Engineering Nanodegree                                        Apr. 2017 - Oct. 2017