Connor Gooding is a senior analytics engineer based in Chicago with 10 years of experience turning messy firmographic data into production-ready insights for enterprise-scale customers. At Grainger he designed Snowflake/dbt data products and a Streamlit-powered tool that helped correct $4.5B in revenue misclassification and now supports $20B+ in account stewardship. He blends hands-on data engineering (PostGIS, GeoPandas, SQL) with practical ML deployment, contributing prompting strategy and domain expertise to Grainger’s first AI Location Review Assistant. Connor has a track record of operationalizing processes—creating SOPs, QA frameworks, offshore transitions, and training content—to make analytics repeatable and auditable. Early work auditing third-party data and self-taught tooling as an intern show a pragmatic curiosity that extends into personal ML experiments on GitHub applying deep learning to real interests. He combines engineering rigor with business-facing storytelling to drive measurable commercial impact.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS) Electrical and Electronics Engineering with Honors, Bachelor of Science (BS) Electrical and Electronics Engineering with Honors at University of Illinois Urbana-Champaign
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