AI Query-to-SQL Annotation for Sports Analytics
Worked on a high-precision AI training project to convert 100+ natural language queries into SQL queries for a sports data analytics platform. Tasks included: Interpreting user queries related to sports events and data Writing perfect SQL queries ("Gold Queries") that return the exact intended results Collaborating with the data science team to ensure domain accuracy Evaluating existing SQL annotations and improving them for correctness and efficiency Following strict quality assurance (QA) and labeling guidelines Working in a Redshift-based environment with real-world sports datasets The output was used to fine-tune and evaluate AI models for semantic parsing and database QA. Emphasis was placed on annotation clarity, accuracy, and reproducibility.