
Data Science graduate skilled in Python and SQL for data cleaning and analysis. Experienced in utilizing statistical techniques and data visualization to extract insights from structured datasets, enabling informed business strategies and improved operational efficiency.
• Cleaned and prepared survey data using Python and R by handling missing values and ensuring consistent formatting
• Performed exploratory data analysis (EDA) to identify trends, patterns, and relationships in customer data
• Applied regression techniques to analyze factors influencing customer behavior and preferences
• Translated analytical findings into actionable business insights to support decision-making
• Wrote SQL queries using SELECT, GROUP BY, and ORDER BY to analyze structured datasets
• Used aggregation functions such as SUM, AVG, and COUNT to compute key performance metrics
• Identified trends and patterns in data to support data-driven insights
• Processed datasets using Pandas for data cleaning, transformation, and preprocessing
• Handled missing values, removed duplicates, and improved overall data quality
• Built visualizations using Matplotlib to effectively communicate trends and patterns
• Extracted meaningful insights from datasets to support business understanding