• Data Forecasting and Machine Learning: Led market share and customer churn forecasting experiments using Python and R on a 100k+ record dataset, achieved 15% better prediction accuracy and reduced customer churn by 5% with machine learning tools like Scikit-learn

• Visualization and Report Management: Developed a dynamic dashboard using SQL, which later was adopted as an internal management tool, to enhance communication and data sharing across organizational teams in 10+ regions and integrated Power BI and Tableau to create customized reports with actionable recommendations for diverse teams across regions

• System Modernization with Alteryx and Automation with Python: Employed Python code for data processing and cleansing using libraries such as Pandas and NumPy, applied predictive analytics using libraries like Scikit-learn, TensorFlow, and PyTorch to construct and deploy predictive models, realized the automatic process of report generation adopted by internal teams across 10+ regions, and led to 30% increase in work efficiency

• Geospatial Data Analysis: Employed Google Maps API to extract geolocation data, categorized the given data using Scikit-learn in Python, and used machine learning algorithms like classification model to help the team identify the optimal cell tower location