Who am I?

Hi! I’m Cody Heintzleman. I’m originally from Destin, Florida and currently based in Lebanon, Ohio. I’m pursuing a B.A. in Organizational Leadership with a minor in Information Systems at Xavier University (expected Aug 2026).

Synopsis

I’m a U.S. Air Force veteran (8+ years) transitioning into the sports industry, where I combine operations, tech, and fan experience. I love building systems that make events run smoothly and using data to improve processes and performance.

Academic Background

  • Xavier University — B.A., Organizational Leadership; Minor in Information Systems
  • Coursework includes BAIS 329 (R programming & Boston Housing dataset), BAIS 360 (Python & analytics), and leadership modules integrating systems thinking and adaptive leadership.

Professional Background

  • Sports Marketing & Operations Associate — Momento (Cincinnati Bengals activations, 2025– )
    Supporting on-site fan experience technology, vendor coordination, and event-day operations.
  • Operations Dispatch Intern — Cincinnati Open (2025)
    Coordinated facilities, key control, radio logistics, and cross-team workflows for a major tennis tournament.
  • U.S. Air Force — Weapons Load Team Manager & Armament Systems Supervisor
    Led teams up to 46 personnel, managed high-value assets, and executed acquisition & IT refresh projects.

LinkedIn: https://www.linkedin.com

Experience with R & Data Mining

  • Comfort level: Learning / Intermediate
  • I’ve used R for data wrangling, summaries, and visualization (e.g., MASS::Boston). I’m growing skills with R Markdown, projects, and reproducible workflows.

Experience with Other Analytic Software

  • Excel (pivot tables, lookups), Python (loops, basics), SQL (intro), and Tableau/Power BI (beginner).

(Optional) A tiny equation

The mean of \(x_1,\dots,x_n\) is
\[ \bar{x} = \frac{1}{n}\sum_{i=1}^n x_i. \]

(Optional) A tiny code chunk

# Demo: summarize and plot some data so the report proves code execution works
library(MASS)
head(Boston)
##      crim zn indus chas   nox    rm  age    dis rad tax ptratio  black lstat
## 1 0.00632 18  2.31    0 0.538 6.575 65.2 4.0900   1 296    15.3 396.90  4.98
## 2 0.02731  0  7.07    0 0.469 6.421 78.9 4.9671   2 242    17.8 396.90  9.14
## 3 0.02729  0  7.07    0 0.469 7.185 61.1 4.9671   2 242    17.8 392.83  4.03
## 4 0.03237  0  2.18    0 0.458 6.998 45.8 6.0622   3 222    18.7 394.63  2.94
## 5 0.06905  0  2.18    0 0.458 7.147 54.2 6.0622   3 222    18.7 396.90  5.33
## 6 0.02985  0  2.18    0 0.458 6.430 58.7 6.0622   3 222    18.7 394.12  5.21
##   medv
## 1 24.0
## 2 21.6
## 3 34.7
## 4 33.4
## 5 36.2
## 6 28.7
x <- rnorm(200)
summary(x)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## -2.5992 -0.5322  0.2362  0.1769  0.8691  2.6544
hist(x, main = "Histogram of x")

Notes for the instructor

  • This report was created in an RStudio Project with the requested preferences:
    • Save workspace to .RData on exit: Never
    • Show margin at column 80
    • Provide R style diagnostics: Enabled
  • Image is referenced via a relative path (images/cody.jpg). If you review locally, ensure the image file exists in that folder.