Shariqa Fatima

Developed machine learning models using Python, Scikit-learn, and Pandas to predict employee performance and growth, achieving 82%+ accuracy. Performed exploratory data analysis (EDA) and feature engineering on 5,000+ employee records to build clean, model-ready datasets. Built and evaluated Logistic Regression and Random Forest classification models using precision, recall, and F1-score metrics. Queried and managed employee data from MySQL and MongoDB databases using SQL for efficient data retrieval and preprocessing. Presented data-driven insights and model findings to stakeholders to support informed HR decision-making.