Data Scientist at Apple

Data Scientist responsible for developing and fine-tuning large language models to power a spend-analysis chatbot, cutting search time by 70%. Built ML models to predict optimal buy cost and supplier for silicon procurement. Architected and deployed end-to-end ETL pipelines processing 500+ jobs daily from multiple sources into Snowflake and MySQL, reducing data latency by 50%. Led classification model development for BOM parts and tiers; implemented CRF, BERT, and REGEX-based pipelines to detect and redact PII and PHI across four data sources with 90% precision. Designed prediction models for In-Store Repair and Mail-In Turnaround Time, and deployed APIs on Apple's Shuri platform (UAT and Production). Maintained IRIS, ISR, and Mail-In APIs; developed a model to forecast Repair Templates; led non-inclusive language replacement initiative within the developer ecosystem.

Data Analyst at UIC - Chicago

Led an ML solution for request tracking to automate routing and responses using topic modeling and auto text generation, reducing response time from 48 hours to 4 hours.