Academic Projects
My academic projects showcase the foundation of my expertise as a data analyst and scientist. These projects highlight my ability to tackle complex challenges with theoretical rigor and technical proficiency, from data modeling and database management to advanced analytics and predictive modeling. Each project demonstrates my ability to turn raw data into actionable insights, leveraging tools like Python, R, and Java.
My academic projects showcase the foundation of my expertise as a data analyst and scientist. These projects highlight my ability to tackle complex challenges with theoretical rigor and technical proficiency, from data modeling and database management to advanced analytics and predictive modeling. Each project demonstrates my ability to turn raw data into actionable insights, leveraging tools like Python, R, and Java.
Predicting Employee Attrition at GE
Predicting Employee Attrition at GE
This project focuses on addressing the critical challenge of employee attrition within a multinational conglomerate. Using data from GE's HR systems, I applied advanced analytical methods to develop a predictive model that identifies key factors influencing turnover.
This project focuses on addressing the critical challenge of employee attrition within a multinational conglomerate. Using data from GE's HR systems, I applied advanced analytical methods to develop a predictive model that identifies key factors influencing turnover.
Key highlights of the project include:
Key highlights of the project include:
- Data Exploration and Preparation: Verified and refined HR data to ensure accuracy, quality, and relevance for actionable insights.
- Predictive Modeling: Built and evaluated models, including Ordinary Least Squares (OLS) regression, Naïve Bayes, Decision Trees, and a Balanced Random Forest, to achieve optimal performance.
- Insights and Impact: Identified predictors such as financial incentives, career growth opportunities, and work-life balance. The findings provided actionable strategies to enhance employee retention, reduce costs, and improve organizational morale.
The project emphasizes a transition from reactive to predictive management, ensuring ethical data use and scalable solutions for attrition management.
The project emphasizes a transition from reactive to predictive management, ensuring ethical data use and scalable solutions for attrition management.
Wildwood Apartments:
Wildwood Apartments:
Modernizing Data Management
Modernizing Data Management
This project addresses the challenges posed by outdated manual systems at Wildwood Apartments, focusing on designing an efficient, scalable, and secure database solution.
This project addresses the challenges posed by outdated manual systems at Wildwood Apartments, focusing on designing an efficient, scalable, and secure database solution.
Key highlights of the project include:
Key highlights of the project include:
- The Paper Problem: Identified inefficiencies caused by manual processes, including data errors, slow operations, and frustrated staff. The analysis showed significant impacts on tenant management, financial operations, and executive decision-making.
- Database Design and Recommendations: Developed a relational database using PostgreSQL, optimized for adaptability, data integrity, and query performance. The design incorporated scalable storage solutions to support portfolio growth while reducing redundancy and enhancing flexibility.
- Enterprise Data Model: Integrated key functionalities such as lease management, financial data tracking, and maintenance workflows to streamline operations and ensure accuracy.
- Security Plan: Proposed a comprehensive security framework, including multi-factor authentication (MFA), role-based access control (RBAC), encryption, and disaster recovery plans, ensuring compliance with federal housing regulations.
The project demonstrates my expertise in database management, design optimization, and implementing secure, scalable solutions for enterprise operations.
The project demonstrates my expertise in database management, design optimization, and implementing secure, scalable solutions for enterprise operations.
Bellabeat Study: Fitness Trends and Marketing Insights
Bellabeat Study: Fitness Trends and Marketing Insights
This project analyzes fitness trends and consumer behavior to provide strategic marketing recommendations for Bellabeat’s fitness tracking device, Time. By leveraging data from Fitbit users, consumer surveys, and Google Trends, the study uncovers actionable insights to optimize Bellabeat’s market positioning and advertising strategies.
This project analyzes fitness trends and consumer behavior to provide strategic marketing recommendations for Bellabeat’s fitness tracking device, Time. By leveraging data from Fitbit users, consumer surveys, and Google Trends, the study uncovers actionable insights to optimize Bellabeat’s market positioning and advertising strategies.
Key highlights of the project include:
Key highlights of the project include:
- Consumer Behavior Analysis: Identified step tracking as the most consistent trend among fitness tracking users, with over half of survey respondents favoring walking or jogging as their primary activity.
- Data-Driven Insights: Analyzed a dataset of Fitbit users, revealing that active days average between 6,000 and 9,000 steps. Supplemented with survey and search data to uncover gaps in user satisfaction, such as inaccuracies in step tracking.
- Strategic Recommendations:
- Focus marketing efforts on Bellabeat’s competitive advantage in consistent step tracking.
- Tailor advertisements based on consumer preferences for reliable tracking and user-friendly features.
- Implement a quarterly review of marketing metrics to refine strategies based on engagement data.
This study demonstrates my ability to integrate multiple data sources into actionable insights, combining analytical rigor with practical recommendations for business success.
This study demonstrates my ability to integrate multiple data sources into actionable insights, combining analytical rigor with practical recommendations for business success.