REHAN ALI MOHAMMED

Results-driven Data Science Intern at DataMinds Technologies, skilled in Python and SQL. Achieved 85% churn prediction accuracy through machine learning model development. Enhanced data visualization for marketing with interactive Tableau dashboards. Proven ability to automate workflows, reducing manual effort significantly, while demonstrating strong analytical and problem-solving skills.

• Research paper published in a peer-reviewed international journal (IJITCE).
• Built NLP models achieving high accuracy in sentiment classification of informal chat data.
• Developed multiple academic and personal projects in machine learning, data analytics, and software development.

• Data Science Research
• NLP Applications
• AI-driven Analytics
• Social Media Data Mining
• Software Development
• LLM

WhatsApp Group Chat Analysis (Research Project), Designed and implemented a fully automated NLP pipeline for unstructured text analysis. Extracted behavioral insights, engagement trends, and emotional tone from chat datasets. Created dashboards to display user activity and communication dynamics. Loan Approval Prediction Using NLP, Developed a machine learning model to predict loan approval status based on applicant financial and demographic data.

1st Place in ISL Engineering College Hackathon, 04/01/24, For developing a real-time text sentiment analyzer.

WhatsApp Group Chat Analysis Using Natural Language Processing (NLP), International Journal of Information Technology & Computer Science (IJITCE), 2347–3657, 13, 2s, 05/01/25, 468–476, Developed a complete NLP framework for analyzing unstructured WhatsApp group chat data. Applied preprocessing (tokenization, lemmatization, stopword removal, emoji handling) and ML techniques for sentiment analysis, topic modeling, and user behavior tracking. Built a visual dashboard with activity trends, heatmaps, and word clouds to support behavioral, educational, and corporate research.