Summary
Koushik Meesala is a data analyst with nine years of industry experience and three years focused on building large-scale analytics and ML solutions using Python, SQL, Spark, and Databricks. At Databricks he architected PySpark pipelines processing over 2.5 billion telemetry events and used MLlib clustering to surface adoption cohorts that directly influenced product strategy and improved DAU and feature adoption. Previously at Gartner he led a churn-prediction initiative that increased accuracy to 88%, protected over $10.5M in ARR, and shortened reporting cycles from days to hours through automated AWS-based ETL. He combines hands-on engineering—ETL automation, Delta Lake optimization, and query performance tuning—with product-minded visualization (Tableau/Power BI) to translate complex signals into operational impact. Based in Charlotte, NC, he brings cross-functional collaboration experience across product, sales, and engineering and a knack for turning behavioral telemetry into measurable business outcomes.
9 years of coding experience
1 year of employment as a software developer
Master of Science - MS Computer Science Major: Data Science and Business Analytics, Master of Science - MS Computer Science Major: Data Science and Business Analytics at University of North Carolina at Charlotte