• Developed and expanded LLM-based application with a RAG system and LangChain to produce a custom chatbot solution• Fine tuned foundational embeddings models on scientific corpus to improve vector representation of domain specific vocabulary with PyTorch• Engineered a recommendation-and-search engine, machine learning models, enterprise data pipelines, RESTful backends, and analytics dashboards for 4 applications with over 1500 total daily active users using Agile methods • Developed and implemented a semantic search and recommendation system using Elasticsearch for an internal Q&A platform while ensuring privacy compliance for 600,000 questions/answers across 500 stakeholders using Elasticsearch and feature engineering • Experimented and tested different machine learning models to identify best models to incorporate into search and recommendation system • Acted as a communication liaison between cross functional teams with diverse technical subject matter experts and non-technical management to facilitate collaboration and streamline development processes • Implemented and iterated on machine learning models to contribute to research as the field evolves by staying up to date with latest machine learning papers • Created and deployed ETL pipelines to cloud using Pandas for transformation, Docker for containerization, and AWS EC2 for deployment • Technical owner of mentorship matching application, collaborated with stakeholders to lead team, manage expectations, and develop pipelines with backend API in Flask • Onboarded and trained 2 engineers on development environment, Agile, and Bitbucket

• Designed a data-driven dashboard that expedited drug manufacturing processes by using Pythonand SQL for data analysis and regression modeling

• Programmed machine learning models analyzing and visualizing 3,900,000 data points across 6,400 files in Python using SciPy, NumPy, Pandas, Matplotlib, Scikit-Learn and other data analysis packages in Linux (CentOS and Ubuntu) environment • Modified data in PostgreSQL RDBMS and learned database schema, tools, and concepts• Tested, trained and implemented diverse regression and classification algorithms• Trained 3 new analysts on data analysis in Python and SQL by teaching use of different libraries, running existing software using Bash scripts in Linux environments, and lab-based software developmen