Bio

I am a recent graduate from Simmons University, holding a double major in Data Science and Analytics and Statistics, with a minor in Public Health. I am passionate about using data analysis and machine learning on global healthcare data to develop innovative solutions for real-world problems. My academic journey has equipped me with a robust set of data science skills, demonstrated through my various coursework and projects. I am particularly interested in using machine learning techniques to uncover insights and drive decision-making in healthcare.

Education

Simmons University | Boston, MA

B.S. Data Science and Analytics & Statistics | August 2020 - May 2024

  - Minor: Public Health 
  
  - Summa Cum Laude 

  - Honors Program 
  

Experience

Research Data Coder | Brigham and Women’s Hospital | January 2022 - Present

Global Technology Analyst | Bank of America | June 2023 - August 2023

Data Entry Intern | Broadstreet Institute | January 2022 - March 2022

Relevant Courses

• Introduction to Computer Science | Fall 2021
• Intermediate Statistics: Design & Analysis | Fall 2021
• Data Structures | Spring 2022
• Introduction to Data Science | Spring 2022
• Data Interoperability | Fall 2022
• Special Topics (Time Series) | Spring 2023
• Regression Models | Spring 2023
• Machine Learning | Spring 2024

Machine Learning Algorithms

• Simple Rules (1Rule)
• Naive Bayes
• Linear Regression
• Logistic Regression
• KNN
• Association Rules
• Decision Trees
• K Clustering
• PCA
• ANN
• Random Forests
• Boosting
• Neural Networks
• SVM

Relevant Coursework

Intro to Data Science - Blogs

1. Do You Like to Dance? | February 2022

2. Data Wrangling 101 | April 2022

3. Save The Bees! | May 2022

Data Interoperability - Use Case

1. College Majors and Their Graduates | December 2022

Special Topics (Time Series) - Final Project

1. Droughts in U.S. | May 2023

Machine Learning - Final Project

1. Obesity Levels Based on Eating Habits and Physical Condition | May 2024