Data Science student at San Jose State University (Fall 2026). Focused on machine learning, NLP, and AI engineering.
NLP-powered tool that analyzes resume-job description fit using TF-IDF keyword matching and LLM-based semantic analysis via Claude API. Features a smart skill taxonomy, AI bullet point rewriter, and interactive dashboard with match scores and skill gap visualizations.
Conversational AI assistant answering natural language NBA questions grounded in real-time stats. RAG pipeline combining structured stat lookups with semantic vector search over 478 player and team summaries.
Full-stack ML app predicting NBA MVP, DPOY, and Sixth Man awards using a custom dataset of 16,500+ game-level records. K-Means clustering classifies 340+ players into performance tiers with interactive leaderboards and radar charts.
Python, SQL, Java, C, C++
LLMs, NLP, RAG Pipelines, Vector Embeddings, LangChain, ChromaDB, Scikit-learn, TensorFlow, Claude API, OpenAI API, Hugging Face, spaCy
Pandas, NumPy, Plotly, Matplotlib, PostgreSQL, BigQuery, TF-IDF, Feature Engineering
Git, Docker, FastAPI, Streamlit, Gradio, AWS, GCP, REST APIs, PyMuPDF
Built and deployed machine learning pipelines in Python to ingest and transform large-scale datasets, engineering features and applying anomaly detection models to power production analytics. Developed AI-driven tooling and automated model workflows that surfaced real-time performance signals, and designed reproducible model training, evaluation, and deployment workflows with standardized documentation.
Diagnosed and resolved hardware, software, and network issues for 20+ customers weekly. Implemented security measures and optimized device configurations across Windows, macOS, and mobile platforms.