Arnav User

I am a computer science undergraduate focused on machine learning, full‑stack development, and applied AI. I build production-oriented tools that turn data into actionable intelligence and automate monitoring and notification workflows.

At Wefire I designed Python-based data pipelines that scraped and analyzed 5,000+ posts for market sentiment using the Google Gemini API and Pandas, identifying 50+ market opportunities. I also created a real‑time Reddit monitoring bot using PRAW and an automated SMTP pipeline that delivered 500+ immediate alerts in a 24‑hour test.

My projects span end‑to‑end predictive modeling, NLP scraping and classification, RAG chatbots, and full‑stack web applications. I’ve implemented models with Scikit‑learn, XGBoost, TensorFlow/Keras and built RAG systems with LangChain and vector stores (ChromaDB/FAISS) to power conversational resume agents.

I enjoy solving practical problems with reproducible pipelines and performant systems — whether reducing API load with caching, delivering real‑time alerts, or deploying ML models — and I seek opportunities where I can contribute engineering rigor and data‑driven product impact.