About

Harlan Seymour is a highly experienced and skilled full-stack engineer with expertise in data engineering, machine learning, and other areas of the tech stack. Currently, he serves as the Founding Engineer at Level, a promising startup in San Francisco. In his role, he is responsible for loan tape ingestion, analytics using TypeScript, dataframe-js, Node.js, and Supabase, credit modeling, and cash flow analytics of loan portfolios, and Node.js UI development. Harlan has a rich professional background, having worked with several renowned companies in the past. He served as a Technical Advisor for AI at Fujita Corporation Japan, where he guided the company on how to best utilize artificial intelligence in their projects. He also worked as the Founding Engineer for Data & Machine Learning at Afresh, where he designed and implemented the data and machine learning foundation for the company as its first engineer after the CTO. At Afresh, he created a bespoke ETL pipeline to ingest daily grocer data and transform it to Afresh format, including health checks, Airflow DAG, and offline utilities. He also created the "recipes" framework to track produce sales within recipes, wrote copious SQL for ETL pipelines, and implemented the "big model" LightGBM quantile ML model to forecast demand for hundreds of produce items across dozens of stores. Harlan holds an MS in Computer Science from the University of California, Berkeley, and a BS in Physics from the University of Illinois. He has over 24 years of relevant experience and is proficient in a wide range of technologies, including SQL, NodeJS, Javascript, ML, Pandas, UI, Data Engineering, ETL, AI, Typescript, Postgres, Apache Airflow, and Senior Software Engineering. With his impressive skills and experience, Harlan is a valuable asset to any organization looking to leverage the latest technologies and stay ahead of the curve.