Data Analyst at Quomatic Solution Limited

Led data collection, cleaning, and preprocessing of sales data for Big Mart Sales Prediction project. Used Python (pandas, numpy) to handle missing values, encode categorical variables, and scale features for model readiness. Performed exploratory data analysis with matplotlib and seaborn to identify patterns and relationships across products, stores, and sales variables. Encoded categorical variables with LabelEncoder and prepared datasets for supervised learning models. Split data into training and testing sets and applied feature scaling. Developed and compared multiple predictive models (Linear Regression, Decision Tree, Random Forest, Gradient Boosting, SVR, XGBoost); selected XGBoost Regressor as the best performing model based on R-squared and cross-validation. Visualized feature importances and model results to communicate insights to stakeholders and support data-driven decisions. Gained experience with end-to-end ML workflow from data preprocessing to model evaluation and dep