AI-Enabled Quality Drift Detection and Engineering Workflow Automation Intern

This internship project focuses on applying data analytics and machine learning techniques to large-scale quality datasets for faster detection of quality-metrics drift. The intern will contribute to an end-to-end solution covering data querying, preprocessing, analytics, modelling, and results visualization. The role involves developing analytical models, creating automated workflows, and producing visualizations to communicate model results and quality trends effectively.