Srishti Srivastava

Developed and deployed NLP models for text classification and topic modeling on large datasets of customer feedback. Built a model to help the Discovery and evolution of all key assets in scope relevant to exploration of data and insights from AI. Designed and implemented an automated text classification system to streamline document processing and identify private or sensitive data. Collaborated with cross-functional teams to identify opportunities for leveraging NLP to improve business outcomes. Optimized machine learning models to improve accuracy and performance on large datasets. Worked under Agile methodologies.

Data Modeling for AT&T AMP: Built Data models per an executive AT&T initiative by working on prioritized application databases. Erwin (a data modeling tool) was used to build the model and to publish into a consolidated metadata repository. Collected as much metadata as possible that relates to persistence and movement. Ability to have all applications use the metadata repository for architecture, development, and defect management. Published approx. 60 schemas.