Graduate student from Northeastern University, Seattle majoring in Data Analytics Engineering with a focus on Machine Learning. Worked previously for about 3 years as a Software Engineer at Capgemini Technology Services, India where I gained experience in development of end-to-end systems on SAP platform and interact with cross-functional teams to implement global solutions. I have developed a keep interest in Deep Learning and Natural Language Processing during my time in the company and in graduate school
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Experience
Worked for 3 years as a Software Engineer at Capgemini Technology Services, India. Experience in SAP ABAP, SAP HANA and SAP Cloud Platform. Worked on migration of teams from on-premise to SAP Cloud and worked on automation of internal activities. Developed a unified service request platform for various cross-functional teams of the client in order to maintain a central repository of requests. Integrated Machine Learning in order to analyze the most common issues and ways to improve resolution time, and Integrated the same with JIRA. Worked on improvement and maintenance of SAP BW and SAP HANA platform in order to enable teams perform their day-to-day activities. Worked on automation of service request creation in Python, thereby reducing the manual processing of over 6000 email a month
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Projects
1. Humanoid Question Answering chatbot
Worked on a humanoid Question Answering Chatbot using Transformer architecture like BERT and integrated the same with the Slack channel of the company. Deployed the model on Google Cloud Platform and equipped with the intelligence to improve with feedback and provide more accurate responses to complex technical questions.
2. Text Summarization using Transformer
Developed a model to preform automatic extractive text summarization of news articles from CNN and Daily Mail dataset using Transformer architecture like BERT. Developed the model using Recurrent Neural Networks like LSTM to compare the performance and deployed the model using AWS platform.
3. Sales Forecasting using Time Series Analysis
Designed and Implemented a machine learning solution to perform Sales Forecasting for predicting revenue based on historical sales, with an accuracy of 90 percent for one of the largest retailers
based out of the Pacific Northwest region using Time Series Analysis methods like ARIMA and LSTM in Python and presented results using Tableau
4. Airlines Performance Evaluation and Prediction of Flight Delay
Created a live, interactive Dashboard using R Shiny and D3.js for analyzing the performance of aircrafts across the country. Applied Random Forest and LSTM to predict the delay of flights and used AWS platform for finetuning and deployment of the model