Vignesh Raja

Formulated an effective model-building strategy in Natural Language Processing (NLP), in the areas of intent classification, entity recognition, text summarization, and topic modeling for Agent Engagement score prediction leveraging Rasa NLU, SpaCy, NLTK libraries. Developed a Natural Language Processing model which performs keyword extraction and categorized the files with technical keywords. Worked on Anomaly Detection using a Time Series Forecasting model using FB Prophet and created visualizations in Kibana. Built a robust Machine Learning Model for predicting Customer Satisfaction score. Created informative dashboards and provided data insights using Data Analytics Tool (Power BI). Key Responsibilities: Developed creative solutions and built prototypes for problems using algorithms based on machine learning, statistics, and optimization in Python. Performed extensive Data Collection, Cleaning, Exploratory Analysis, Visualization.

Devised a text parser for extracting details from resumes and performed Named Entity Recognition (NER). Designed a contextual question answering model using Botpress. Migrated an in-house website to GCP using Google Compute Engine and Cloud SQL. Created a chatbot for internal ticket creation using Rasa NLU. Key Responsibilities: Extended ML libraries and frameworks to apply in NLP tasks using Python. Worked on web frameworks and creation of API services using Flask. Experienced in working in an Agile development Environment.

Member, IEEE Computer Society; Member, Graphics Design team