Data Science Intern
Current- Streamlined AT&T’s spam detection workload by implementing a Python-based machine learning model with natural language processing, while using K-Means clustering to optimize category classification and improve accuracy
- Increased resolution rates of identity investigations by 25% by utilizing Excel and Python to identify trends in verification failures, and streamlining the manual investigation process for the Operations team