Kendall Gillies is a Data Science Manager with 9 years of experience blending deep mathematical training and hands-on data engineering to deliver reliable, scalable analytics pipelines. At Numerator he led projects that preserved panel continuity, built lag-adjustment and forecasting models, and established foundational repos, Snowflake schemas, and Airflow orchestration that still support production. He’s known for reducing friction between Data Science and Data Engineering by creating reusable libraries, demographic weighting tools, and automated workflows that improve data quality and free teams to focus on high-value work. Prior roles at Home Chef and PNNL showcase his ability to harden ingestion pipelines, integrate diverse data sources, and apply advanced statistical methods from A/B testing to Bayesian sensitivity analysis. Based in Farragut, Tennessee, Kendall combines academic rigor (PhD in Mathematics) with practical engineering craft and a knack for turning ambiguous data problems into dependable operational products.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Arts (BA), Mathematics, Bachelor of Arts (BA), Mathematics at Texas Tech University
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