1. Led the development of a sophisticated E-Billing Assistant leveraging Machine Learning (ML) to enhance the efficiency of billing processes. The project consisted of two key phases: Identification and Remediation.2. Led the development of the Circle of Growth (CCOG) Score Tool, a transformative solution designed to measure employee performance objectively.3. Embarked on the creation of a robust tool to streamline the identification of Ideal Customer Profiles (ICP) by automating the… Show more 1. Led the development of a sophisticated E-Billing Assistant leveraging Machine Learning (ML) to enhance the efficiency of billing processes. The project consisted of two key phases: Identification and Remediation.2. Led the development of the Circle of Growth (CCOG) Score Tool, a transformative solution designed to measure employee performance objectively.3. Embarked on the creation of a robust tool to streamline the identification of Ideal Customer Profiles (ICP) by automating the Exploratory Data Analysis (EDA) process4. Undertook the creation of an innovative tool designed to automate data extraction from website content, integrate conversational Al capabilities, and perform tasks without the need for manual intervention. Show less

Automated Tool for Operations and Management.➢ Deployed advanced Machine learning algorithms to classify the various incident classes using NLP and other techniques.➢ Provided the analytical solution with sentiment analysis using Microsoft cognitive services and recommended KB articles using the BOT framework.➢ Helps to reduce the resolution time and manage the priority\assignments of theincidents.Data Collection➢ Conducted extensive research on manual ticket… Show more Automated Tool for Operations and Management.➢ Deployed advanced Machine learning algorithms to classify the various incident classes using NLP and other techniques.➢ Provided the analytical solution with sentiment analysis using Microsoft cognitive services and recommended KB articles using the BOT framework.➢ Helps to reduce the resolution time and manage the priority\assignments of theincidents.Data Collection➢ Conducted extensive research on manual ticket management and classification methods used in ServiceNow and CRM.➢ Gathered classified data from different aggregators by querying in Azure SQL.Data Wrangling & Visualization➢ Cleaned, merged and manipulated datasets and conducted feature engineering using Pandas.➢ Created various charts using Matplotlib and Seaborn to perform a preliminaryanalysis of the collected data.➢ Used matplotlib\Seaborn to create real-time ROI graphs that helped the teams focus on high-priority tickets. This led to a 20% increase in response time. Show less

➢ Deployed experiments and webservices to classify the incidents raised in service now.➢ Collected data from various sources including the ServiceNow and SQL database.➢ Increase the overall productivity by providing faster resolution of tickets.Data Collection➢ Ability to write complex SQL queries to gathered data from different databases.➢ Analyzed issues within the database and be able to fix it within SQL.Azure ML Studio - Classification Modeling➢ Models… Show more ➢ Deployed experiments and webservices to classify the incidents raised in service now.➢ Collected data from various sources including the ServiceNow and SQL database.➢ Increase the overall productivity by providing faster resolution of tickets.Data Collection➢ Ability to write complex SQL queries to gathered data from different databases.➢ Analyzed issues within the database and be able to fix it within SQL.Azure ML Studio - Classification Modeling➢ Models trained and developed in Azure ml studio based on 80% prediction rate.➢ Deployed the predictive experiment and generate the webservice to predict the classes.➢ Predicted classes 25% better than traditional figures.➢ Tested and implemented decision trees, random forests and ensemble models via bagging and boosting. Show less