I'm a Data Scientist and Machine Learning Engineer currently in my 6th semester of Computer Science & Business Systems at Academy of Technology, West Bengal. Beyond academics, I'm a recognized Kaggle Expert — a competitive title earned through notebook medals and strong finishes on real-world datasets, not just coursework.

My work spans the full ML pipeline: cleaning messy data, engineering features, training and tuning models, and deploying them as production-ready APIs that real users can interact with. I build primarily in Python, using PyTorch for deep learning, Scikit-Learn and XGBoost for classical ML, and FastAPI for model serving. I've built and deployed five live projects covering fraud detection, medical imaging, rent prediction, customer churn, and NLP-based recommendations — each with a public URL, not just a GitHub link.

I also authored DataDiagnose, an open-source Python library published on PyPI. Built with zero external dependencies, it automatically diagnoses ML datasets — detecting 8 types of data quality issues, generating a 0–100 health score, and recommending the right model type before training begins. It's the kind of tool I wished existed when I started, so I built it myself.