Jared Brotamonte

Recent Graduate of Northern Arizona's class of 2024 with a strong background in statistical modeling, machine learning, and programming. Adept at utilizing various data analysis tools to extract insights from complex datasets. Experienced in developing and deploying predictive models, performing exploratory data analysis, and communicating findings effectively. Eager to leverage academic knowledge and practical skills to drive data-driven decision-making and solve real-world problems. Committed to continuous learning and staying up-to-date with the latest data science techniques and technologies.

Pick-My-Meals - Group Project

• Developed a user-friendly website that allows customers to curate personalized meal plans based on dietary preferences and ingredient filters
• Utilized Python, Firebase database, and HTML for backend development, data storage, and front-end design
• Collaborated effectively in a team of 5, applying software engineering principles and project management methodologies

Technologies: Python, Firebase, HTML, CSS, Web Development, Collaborative Software Development, Agile Methodologies

NYPD Arrest Data Analysis

• Conducted a comprehensive analysis on the NYPD Arrest Data 2023 dataset to investigate potential racial biases in law enforcement practices
• Performed data cleaning, variable transformation, and factor level consolidation to prepare the dataset for modeling
• Implemented multiple modeling techniques, including Linear Discriminant Analysis (LDA), Random Forest, Multinomial Logistic Regression, and K-means Clustering
• Evaluated model performance, identifying significant predictors such as offense description, arrest date, location, and jurisdiction code
• Critically analyzed the limitations of the dataset and the challenges posed by categorical variables
• Provided insightful conclusions, acknowledging the need for additional data sources to directly investigate potential biases in law enforcement

Technologies: R, Data Cleaning, Exploratory Data Analysis, Statistical Modeling, Machine Learning

TikTok Video Virality Analysis

• Conducted exploratory data analysis on a dataset of over 2,800 TikTok videos to investigate the factors influencing video popularity and engagement
• Performed data visualization techniques, including scatter plots and word clouds, to uncover patterns and insights related to video likes, comments, shares, hashtag usage, and account metrics
• Employed statistical modeling techniques, such as backward stepwise regression, to identify the most significant predictors of video likes, including comments, shares, and video length
• Designed an informative poster summarizing key findings, visualizations, and actionable insights for content creators and marketers on TikTok
• Presented the research at the Northern Arizona University Undergraduate Symposium, effectively communicating complex data-driven insights to a diverse audience

Technologies: Data Analysis, Data Visualization, Statistical Modeling, Regression Analysis, Poster Design, Public Speaking, Presentation Skills