Brandon Hill
Rutgers University 2024
B.S. Degree in Applied & Computational Mathematics, Computer Science Minor
As an applied mathematics major and computer science minor at Rutgers University, I'm passionate about leveraging my skills in data analysis to solve complex problems. My studies have equipped me with the skills to translate real-world data into actionable insights.
Beyond academics, I've gained valuable experience in the healthcare industry, fostering a strong interest in its data-driven future.
When I'm not exploring datasets, I can be found hitting the trails for a hike, pounding the pavement for a run, or hanging out with my two cats.
My Skills
Building bridges between data and decision-making with a versatile skillset.
Technical Skills:
- Data Analysis: Python (including libraries like Pandas, NumPy), SQL, Excel
- Data Visualization: Tableau, Matplotlib, PivotChart, Powerpoint
- Version Control: Git, GitHub
- Machine Learning & Algorithms: Familiarity with machine learning concepts and algorithms (including linear and logistic regression, decision trees, KNN, optimiztion, clustering analysis, and model evaluation)
Analytical Skills:
- Data Analysis & Statistical Modeling: Ability to clean, analyze, and interpret data using various statistical methods.
- Problem Solving: Skilled at identifying trends, patterns, and insights from data to solve complex business problems.
- Business Acumen & Analysis: Understanding of key business metrics and translating data insights into actionable recommendations.
Communication Skills:
- Reporting & Dashboarding: Ability to create clear, concise, and visually appealing reports and dashboards for various audiences.
Diabetes Predictor
This project explores the use of machine learning to predict diabetes in female Pima Native Americans. I leverage a public health dataset to build and evaluate Decision Tree, Logistic Regression, and Random Forest models for patient classification. Source code and analysis steps are documented within a Jupyter Notebook, allowing viewers to explore and visualize relevant data and models.
Visualizing Global Life Expectancy and Socio-Economic Factors (World Bank Data)
This project explores the relationship between life expectancy and socio-economic factors across countries using World Bank data.
Here, I leverage data tools such as Tableau and Jupyter Notebooks to identify trends and patterns, uncovering potential correlations between factors like income, education, and health outcomes.
Delivering Functional Requirements & User Stories
Bridging the gap between business needs and technical execution is key.
Below, you'll find examples of my work in creating comprehensive Functional Requirements Documents (FRDs) and detailed User Stories (US) during my time at Rutgers University.
These artifacts capture business needs, define system functionalities, and ensure a user-centric approach to development. See how I leverage data analysis to inform these documents, guaranteeing alignment between business goals and user experience, as demonstrated in my work for the hypothetical Park Company.
Validating Fresnel's Equations
This project investigated the experimental validation of Fresnel's Equations for P-polarized light.
Fresnel's Equations predict the intensity of reflected and transmitted light based on the incident angle. Our approach involved measuring Brewster's angle, the angle at which there is no reflection for P-polarized light, and the refractive index of glass. These experimental values were then compared to the theoretical predictions from Fresnel's equations. By analyzing the percent difference between theoretical and experimental results, we aimed to assess the accuracy of Fresnel's Equations for P-polarized light.
Contact Me
Feel free to check me out on GitHub, read over my resume, or reach out on LinkedIn!