Summary
Nathaniel Speiser is a Senior Associate Data and Analytics Modeler with nine years of experience combining a rigorous physics background and practical data engineering to deliver production-ready analytics and ML pipelines. He leverages deep mathematical grounding from condensed-matter research to build robust ETL and ML systems—recently leading metadata-driven Databricks pipelines and a production AWS Glue/PySpark migration for healthcare data. Comfortable across Python, SQL, NLP, and visualization tools, he has built prototype and production NLP topic models and sentiment analyzers, and a suite of migration tools for dashboard infrastructure. Nathaniel pairs hands-on model development with cross-functional collaboration, translating domain complexity into auditable, repeatable solutions for clients. Based in Seattle, he brings a scientist’s curiosity to business problems and a track record of turning research-caliber analysis into scalable, client-facing products.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Physics, Bachelor of Arts - BA, Physics at Northwestern University
Master of Science - MS, Physics, Master of Science - MS, Physics at University of Colorado Boulder