Nathan Morse

PhD Student in Political Science at Penn State University


Associate for Assessment, J. Wayne Reitz Union, University of Florida

April 2017 - May 2019. Data scientist for major student affairs department. Managed large databases (~30,000 rows) and coded complex data manipulation processes; ran statistical tests, fit data to models, and formulated assessment metrics to gain insights; designed reports, data visualizations, and graphics; gave oral presentations to administrators; calculated employee performance indexes and determined areas of improvement for trainings; built automatic monthly report system in R with aggregated satisfaction scores for hotel; discovered factors that maximize budget efficiency for weekly GatorNights program using an attendance model, and discovered factors that maximize budget efficiency using an attendance model.


Employee Evaluations Analysis

July 2018. I was tasked with compiling and designing an annual report based on employee evaluations. The goal was to create a report that was deep and informative yet minimalist and attractive. The document includes unique data visualizations, graphs, tables, performance metrics based on a model I derived, and statistical tests that identified potential areas of improvement.

Automatic Monthly Report

July 2018. I created a satisfaction status report for the building’s hotel that can be automatically generated each month. The report, which is entirely coded in R, downloads survey responses from Qualtrics (an online survey platform) using an API token, cleans up the data using tidyverse functions, and produces a single-page infographic using grid functions. I coded nearly all of the project myself, with support from my supervisor when needed, and I designed the graphics. The only component of the report that requires manual human input is the qualitative comments. Other than that, this report can be produced at the click of a button each month to update the Hotel Manager, Business Director, and university officials on customer satisfaction.

Attendance Modeling

December 2017. This joint project for class and work analyzed a year’s worth of data from a weekly entertainment event for students at the University of Florida. I built a linear regression model to predict attendance and determine which factors had the greatest effect on attendance. The insights from this study are helping programmers maximize attendance and budget funding strategically throughout the year.

GatorNights Program Report

July 2018. I was tasked with compiling and designing an annual report for GatorNights, a weekly program for students. My goal was to create a report that was deep and informative yet minimalist and attractive. The document includes unique data visualizations, graphs, tables, and satisfaction scores based on a model I derived.


nam@psu.edu

203 Pond Lab, University Park, PA 16802