Worked on various AI/ML use cases - 1. Built data pipelines in spark and airflow to process the large timestamp data within least possible amount of time. The cloud platforms used for this includes Databricks, Oracle spark cluster and AWS EMR.2. Conceptualised and built the pipeline and algorithm for defining a single index for regions by combining multiple datasets from various sources. 3. Built leadscoring engines for client based on their lead forms data. Used Explainable-AI tools to make the model trustworthy.4. End-to-end pipeline for processing large pdfs using OCR.5. Location intelligence use cases like audience segmentation, deduplicating location data, evaluation scripts for different datasets. The data size ranges from 10 gb to 100gb

Shadowed a project on consumer segmentation in hair care segment using semi supervised model.Worked on consulting and data engineering role for a web app which is suppose to show growth opportunities for a CPG client.

Worked on core AI/ML projects like data extraction from scanned images through OCR. Created and delivered a full stack application of a Warehouse Mangement System, key component being the indoor navigation system in warehouse.

This internship was held under LTI at COE (Centre Of Excellence), VJTI.