About Me
Enthusiastic Data Analyst with strong skills in Power BI, SQL, and machine learning in Python and R. With an 8-month internship in data analysis, I specialize in transforming complex datasets into clear, actionable insig…
Enthusiastic Data Analyst with strong skills in Power BI, SQL, and machine learning in Python and R. With an 8-month internship in data analysis, I specialize in transforming complex datasets into clear, actionable insights to support decision-making processes. Experienced in building dynamic data visualizations and applying machine learning models to solve business challenges, I am eager to contribute to optimizing processes and driving growth through data-driven strategies.
Experience
Data Analysis Intern
<p>Developed and maintained dynamic Power BI dashboards and reports to support data-driven decision-making processes.<br>
Cleaned, transformed, and modeled data using Power Query to ensure accurate and optimized reporting.<br>
Created custom visualizations such as bar charts, pie charts, scatter plots, maps, and slicers for clear and actionable insights.<br>
Wrote DAX formulas and developed measures to perform advanced calculations and enhance report interactivity.<br>
Assisted in data analysis by integrating various data sources, improving operational efficiency.<br>
Applied data cleaning techniques to large datasets, ensuring high-quality data for business intelligence reporting.<br>
Developed and implemented machine learning models using Python and R for predictive analytics and business insights.<br>
Applied supervised learning techniques such as linear and polynomial regression to forecast outcomes and improve decision-making processes.<br>
Evaluated model performance using validation metrics like MAE, MSE, RMSE, and R-squared for regression models and Precision, Recall, F1 score for classification models.<br>
Leveraged Principal Component Analysis (PCA) to reduce dimensionality and enhance model efficiency in both regression and classification tasks.<br>
Utilized SQL for data extraction and preprocessing, ensuring clean and structured data for machine learning algorithms.</p>