Data Scientist
Current- Developed a dynamic air quality monitoring application using Python, integrating Tkinter for a user-friendly interface and the Open-Meteo API for real-time AQI data. Leveraged Pandas for efficient data manipulation and Matplotlib for clear, impactful data visualizations.- Engineered an automated ETL pipeline to power a real-time, data-driven plant science dashboard using Dash. Implemented Beautiful Soup for web scraping, Pandas for data transformation, and utilized Matplotlib, Plotly, and Seaborn to create visually compelling and interactive data visualizations.- Performed data sourcing, cleaning, transformation, advanced calculations, and k-means clustering using Python libraries (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn) to deliver actionable insights.