I am a data science and machine learning enthusiast with hands-on experience in Python, SQL, and NLP-based analytics. I have worked on building and evaluating machine learning models, sentiment analysis pipelines, and data-driven solutions that improve workflow efficiency and support better decision-making.

I enjoy turning raw, unstructured data into actionable insights. My experience includes search intent analysis, trend forecasting, dataset curation, and model evaluation for AI-generated outputs, which has strengthened my ability to work with both structured and unstructured information.

I have practical exposure to tools and libraries such as Pandas, NumPy, Scikit-learn, NLTK, Plotly, Matplotlib, MySQL, and Power BI. I also use Git, GitHub, VS Code, and Jupyter Notebook regularly for development, analysis, and collaboration.

My project work includes building a client subscription prediction model, designing an employee attendance and payroll management database, and creating a credit card insights dashboard. These projects helped me develop skills in predictive analytics, database design, SQL optimization, and data visualization.

I am currently pursuing a B.Tech in Computer Science and Data Science, and I have completed internships in data science and post-LLM training. I am comfortable working on analytical, machine learning, and data engineering tasks in collaborative environments.

I am looking for opportunities where I can continue growing as a data professional, contribute to impactful analytics and AI initiatives, and apply my technical skills to real-world business problems.