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Brigham Eaquinto

    


"Education is freedom" "Excellence"



Finished Projects

R Bootcamp

Current Projects

GitHub

Future Projects

SQL

Scikit-Learn

Statistics

Python

Bash & Powershell


Current Employment

Employment History

Python R BYU-Idaho BYU-Idaho BYU-Pathway
Idaho National Laboratory

High Performance Computing Team

April 2023 – Present

  • Spearheaded development of AI-powered chatbot with the objective of streamlining the IT Help Desk process by leveraging existing data and open source large language models
  • Deployed chatbot ML model on server by building API infrastructure to send user requests, search database, and return model output
  • Integrated API calls to extract tech support ticket history, employing regular expressions for data parsing and cleaning to ensure accurate and relevant information for better chatbot outcomes
  • Built admin dashboard with numerical and graphical summaries for model and system analysis using PlotlyJS
DataThink

Data Consultant

January 2023 – Present

  • Engineered report automation package to read and wrangle data to output reports in seconds, empowering clients with numerous company reports within seconds, resulting in a monthly time savings of over 20 hours
  • Seamlessly transitioned proprietary software-based visualizations to open-source alternatives, delivering substantial cost savings of hundreds of dollars per month to clients
Research Business & Development Center

Data Lead

September 2022 – April 2023

  • Designed and created PowerBI report for school Board of Trustees and Superintendent on financial management, HR, and student achievement by utilizing measures in DAX resulting in greater school funding
  • Developed data model incorporating multiple data sources to provide reporting capabilities including compelling visualizations and data summaries
  • Met with stakeholders to understand requirements and effectively communicated findings to various audiences
  • Instructed team on PowerBI and DAX; ensured team members were included and excelled by finding natural strengths for greater success
BYU Idaho

Data Analyst

April 2021 – December 2022

  • Automated semester reports, saving 3+ weeks of manual reporting each semester by developing reusable R scripts for efficient, high-quality results in every use
  • Led development of tri-university reporting suite using Power BI focusing on retention of online students; reports were utilized by Institutional Research, University Presidential Council for more informed executive decisions
  • Prepared reusable weekly and monthly reports to Student Life executives on program KPIs and past expenditures by automating data pipeline from Qualtrics and university data warehouse to report deployment
  • Guided a team of 5 other analysts in professional development, data manipulation skills, and data visualization theory while fostering a positive work environment
BYU Pathway

Data Scientist

January 2022 – April 2022

  • Created ML model using scikit-learn to predict student retention ensuring maximum model performance; the model was implemented university-wide
  • Leveraged topic modeling to label text data using NLP packages, enabling the use of 10% more features incorporated in the student success prediction model
  • Quantified and modeled student KPIs by statistical measurements for effective and reusable progress tracking, increasing faculty effectiveness by 30%

Fun Zone

Brigham Eaquinto's Projects

brighameaquinto.github.io icon brighameaquinto.github.io

Introductory R for data science course. Specifically, reading in, wrangling, and visualizing data using the tidyverse ecosystem.

byu-i-ds-program icon byu-i-ds-program

Personal project exploring the uses of Quarto to organize my learning at BYU-Idaho

cse450-course icon cse450-course

Public facing course materials for CSE 450 - Machine Learning

statistics-notebook icon statistics-notebook

This began as the textbook for Intermediate Statistics (Math 325) at BYU-Idaho. It aims to become a personal notebook for performing and interpreting statistical analyses in R. Contributions and ideas for improvement are welcome.

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