Mohammed Zeeshan Mulla

Developed an ETL pipeline for detecting Image copyright infringements. Achieved 75% accuracy on a deep learning computer vision model for hand signs. Achieved 96% accuracy for text classification model on news stories. Worked on a PoC to quantify gender diversity in news articles. Trained on CNN, LSTM, and Object detection for hand signs. Worked on PoC to quantify State of Art Algorithm performance.

Worked as a data warehouse tester for a migration project from Rdbms to Hadoop. Built a pipeline utilizing Scikit-Learn’s Isolation Forest Algorithm for Anomaly Detection on techmag.com metrics. Created monthly reports in Tableau, leading to increased profitability. Performed Churn Prediction for Retail & Users. Finalist in ‘Informatica Premier League’.

Worked as developer for a data exchange project. Delivered analytical reports contributing to $50K+ in annual recurring revenue. Automated monthly insight generation using Python and SQL, reducing FTE by 20%. Developed analytical and ML models (gradient boosting) to identify influential population. Increased operational efficiency by 30% by optimizing processes and documenting SOPs.