I've built end-to-end data pipelines, machine learning systems, and analytical dashboards across consulting, government, and technology. At Frontier Design, I automated client reporting in Python, saving hundreds of hours of manual work and improving visibility into donation-program effectiveness.
I designed Databricks NLP pipelines for large-scale sentiment analysis, Tableau dashboards for conflict and visa-processing analytics, and AWS infrastructure deployed through Terraform. I also supported uplift testing for unreleased LLM models and led analysis of large financial datasets for a Big Tech client.
Previously at PwC and Grant Thornton, I developed data-validation frameworks, tax-form automation, web-scraping workflows, and SQL solutions for datasets exceeding one billion records. I enjoy carrying work from raw ingestion and transformation through statistical modeling, visualization, and automated reporting.
