Saira Rani

I am an entry-level Data Science and Analytics professional with hands-on experience building end-to-end machine learning and analytical models using real-world datasets. I focus on data preprocessing, feature engineering, model evaluation, and performance optimization across classification, time series forecasting, NLP, and fraud detection.

My project work includes customer churn prediction, high-accuracy sales forecasting, LSTM-based sentiment analysis with GloVe embeddings, and an ensemble credit card fraud detection system. I delivered measurable results such as 78% churn prediction accuracy, R² of 0.9964 for sales forecasting, 90.07% validation accuracy for sentiment classification, and ROC-AUC of 0.93 for fraud detection.

I am proficient in Python-based analytics and visualization tools (Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow/Keras, Matplotlib, Seaborn) and hold multiple industry certifications. I bring a practical, reliability-focused approach to modeling and translating raw data into actionable insights for business impact.