Resume to Job Matcher, Python, Transformers, TF-IDF, RAG, FastAPI, BeautifulSoup, Selenium, Present, Engineered a large-scale NLP pipeline that ingested 50,000+ job postings using transformer and TF-IDF embeddings, Enhanced semantic ranking, raising top-5 match precision from 0.68 to 0.91 while reducing false positives by 41%, Automated job-posting extraction using BeautifulSoup and Selenium with dynamic-content handling, Implemented a TypeScript/React prototype UI for end-to-end workflow testing and validation Earnings Call NLP Pipeline, Python, spaCy, BERT, BART, Pandas, WRDS, Present, Built an NLP system analyzing 44k+ earnings call transcripts to identify forward-looking AI adoption intent, Consolidated director, financial, and transcript datasets using key-identifier matching for unified modeling, Validated a three-layer classification pipeline (regex → FinBERT → BART) with human-in-the-loop checks achieving a 0.93 F1 score Options Pricing API, Python, FastAPI, yFinance, React, Docker, AWS, 11/01/25, Developed 15+ option-pricing and Greeks endpoints with <20ms median latency via optimized numerical routines, Deployed a containerized API on AWS EC2 with Nginx + SSL, sustaining 1,000+ test queries without degradation, Integrated a TypeScript/React frontend enabling real-time options pricing visualization Snowflake Data Engineering Pipeline, Snowflake, SQL, 10/01/25, Architected a Bronze/Silver/Gold warehouse pipeline reducing query times by ∼25% via clustering and optimized SQL, Reduced warehouse compute costs by ∼20% through partition-aware storage modeling, Streamlined multi-step SQL transformations, cutting manual data preparation time by ∼80%