Developed using Google Gemini for data summarization, translation, PII redaction, and classification.
Improved recruitment efficiency by 25% through automated data processing.
Developed a system using Python for efficient network resource allocation.
Utilized libraries for time series data analysis, deep learning (LSTM, Transformers), machine learning, and data visualization.
Achieved a 15% increase in network resource utilization efficiency.
Conducted comprehensive data analysis for an e-commerce company using Python and SQL.
Provided actionable insights that led to a 10% increase in sales.
Automated reporting processes, reducing the time spent on data extraction by 50%.
Developed a machine learning model to predict customer churn using Python and SQL.
Improved prediction accuracy by 20% using advanced feature engineering techniques.