Anthony Steven Lopez

Data Analyst with a solid foundation in Python, SQL, and data visualization, honed through practical experience in data science projects and coursework at Rutgers University's Data Science Bootcamp. Skilled in leveraging data to drive business decisions, particularly in operational optimization and data analysis. Experienced in building ETL pipelines, analyzing financial and health data, and creating interactive dashboards for actionable insights. Passionate about applying analytical skills in the healthcare or finance industries, eager to contribute to a dynamic, data-driven team. Proficient in using a range of data analysis and visualization tools to deliver impactful insights that drive business growth and improve operational efficiency.

Stock Analysis of the American Phone Market

Technologies: Python, Yahoo Finance API, Matplotlib

• Analyzed Apple and Samsung stock performance during the COVID-19 pandemic, identifying recovery patterns and volatility shifts.
• Calculated annualized volatility, revealing Apple's higher volatility but quicker recovery compared to Samsung.
• Visualized stock behavior using 30-day rolling volatility plots and histograms, showing the market’s impact on stock trends.
• Evaluated stock growth, with Apple’s 612% increase, outperforming Samsung (162%) and the tech sector (231%).

Crowdfunding ETL Pipeline
Technologies: Python, PostgreSQL, Pandas

• Built an ETL pipeline to process and store crowdfunding data in PostgreSQL, reducing data processing time by 20%.
• Optimized data storage and reporting, creating a structured database to handle large volumes of data.

Flu Trends Analysis and Visualization
Technologies: Dash, Plotly, Python, SQLAlchemy

• Developed an interactive dashboard using Dash and Plotly to track U.S. flu trends, assisting public health officials in identifying high-risk areas.
• Integrated CDC FluView data and added age group and region filtering for more targeted health interventions.

Employee Attrition Prediction Using Supervised Machine Learning
Technologies: Python, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn

• Built a machine learning model to predict employee attrition, achieving 86.68% test accuracy.
• Identified key factors (e.g., job satisfaction, compensation) affecting turnover, and used Random Forest and Logistic Regression for prediction.
• Performed hyperparameter tuning and evaluated models using accuracy, precision, recall, and F1-score.

Certificate in Data Analytics
Rutgers University, February 2025

• Completed Data Analytics Bootcamp: Earned a Certificate in Data Analytics from Rutgers University in February 2025, where I gained hands-on experience with tools like SQL, Python, Excel, and data visualization techniques.
• Capstone Project: Successfully completed a capstone project analyzing a real-world dataset, identifying key trends, and presenting findings through data visualization and statistical analysis.
• Data-Driven Decision Making: Applied analytical skills to solve complex problems in previous roles, including using data to identify customer behavior patterns that led to a 10% increase in sales in my last position as a sales associate.
• Team Collaboration: Worked in team-based projects during the bootcamp, contributing to collaborative problem-solving and refining my communication skills to explain technical findings to non-technical stakeholders.