Data Scientist

Technical Skills: Python, SQL, R, SAS, C++, MS Excel, Tableau, Machine Learning, Predictive Modeling, Data Cleaning, Statistics, Linear Algebra

Education

Maryville University, St. Louis, MO

• 3.92 GPA
• B.S. in Data Science
• Currently pursuing a Masters in Artificial Intelligence (AI)

Work Experience

UNCOMN, O’Fallon, IL, Data Engineer

• September 2024 - PRESENT
• Provide data support to develop reports and visualizations using Databricks, Python, SQL, and Qlik Sense
• Analyze data requirements, build data models that utilize CI/CD practices, and create data pipelines and ETL processes

UNCOMN, O’Fallon, IL, Computer Science Intern

• June 2024 - September 2024
• Worked alongside fellow interns to develop a pricing tool application that automated and accelerated the process of generating contract proposals
• Developed database and key architecture documentation
• Wrote SQL scripts for database management and querying in Azure SQL and AWS
• Contributed to web development using Angular (JavaScript, CSS, HTML) and Python
• Actively participated in project code reviews

Gonzalez Companies LLC, St. Louis, MO — Engineering / IT Summer Internship

• May 2022 - August 2023
• Supported data gathering and data visualization projects using Python and MS Excel
• Went to different locations to help gather data

City Scoops Creamery, Edwardsville, IL — General Manager

• January 2020 - May 2024
• Became general manager of new store location in August of 2020
• In charge of stock, as well as train and supervise employees at my store location
• Communicate with employees and customers to solve on-the-job problems that arise daily

Projects

Python Project

In the course of this project, I explored university data to conduct an extensive analysis encompassing various facets, including the demographic distribution of students based on their majors, graduation rates by major, assessment of the current students’ Grade Point Averages (GPAs), and an examination of the grade distribution correlated with different instructors.

R Project

In this R project, I analyzed Permanent Magnet Synchronous Motors (PMSM) temperature data. Steps included importing and cleaning the dataset, transforming variables, and exploring summary statistics for ‘pm’ and ‘motor_speed.’ I conducted correlation analysis between these variables and employed ggplot2 for data visualization. Linear regression models were built with varying predictors, and their coefficients and adjusted R-squared values were examined. Additionally, I implemented the k-Nearest Neighbors (k-NN) algorithm to predict ‘stator_yoke’ and evaluated model performance. This project integrated data manipulation, exploratory analysis, statistical modeling, and machine learning to gain insights into PMSM temperature dynamics.

Excel Project

For this Excel project, I analyzed an employee database, employing advanced sorting and filtering techniques. Subsequently, I crafted a comprehensive pivot table detailing salaries, an annuity table, and an interest rate chart. These individual components converged into a final, cohesive analysis for each employee. This dynamic analysis empowers users to efficiently search for specific employees, providing crucial retirement insights, including their retirement goal and proximity to achieving it.