At Zaalima Development Pvt. Ltd., I analyzed large datasets with SQL and Python, refactoring queries to reduce execution time by 25%. I also built data quality checks that reduced errors before stakeholder reporting.
For my AI-Powered Customer Feedback & Churn Risk Flagging project, I built a Python pipeline to process customer reviews and used the OpenAI API to classify sentiment, issue categories, and urgency. I flagged high-urgency negative reviews and visualized issue trends in Power BI.
In my Predictive Feature Adoption Model project, I engineered behavioral features in SQL and trained an XGBoost classifier to predict feature adoption. I also grouped users by adoption likelihood and created a sample targeted-notification payload for low-probability users.
