Wells Fargo is a 3 Trillion asset Bank, a highly sensitive project. Data is taken from various sources and consolidated to provide a futuristic & decisive approach for the organization to follow up. This was basically a Q&A system where user can ask questions and service will respond based on trained data.

Customer is worlds biggest telecommunication provider and customer wants to roll out the specific 5G customer who wants to churn from 4G to 5G. Predict customers who are going to churn and find out the factors that are leading to churn based on the customer feedback reports.

BMW is a highly sensitive project for the Accenture leadership. Reports being generated give an idealistic approach to the leaders about the know-how of the companys performance. Data is taken from various sources and consolidated to provide a futuristic & decisive approach for the organization to follow up.

Metrolinx is a crucial project for the E-Ticketing It provides a well view and appealing reports in dashboards and further taken to extreme levels. Data is taken from various sources and consolidated to provide a futuristic & decisive approach for the organization to follow up.

Quality Improvement Plan/Central Clarity comprises of building a Data Warehouse with periodic updates, enabling the automation of several reports on a monthly basis.

This was basically a Q&A system where user can ask questions and service will respond based on trained data.
Technique applied - Used TF/IDF approach (NLTK, Pandas) and deep learning algorithm Word2Vec for creating word vectors and to get sense of question data & respond with correct answer.

I used two approach:-

1. LDA modeling with elastic search.(Which was not effecient).

then i tried with:-

2. RNN + GRU

Still i am working on that..

• Responsible for implementing data mining and statistical machine learning solutions to various business problems.
• Analyze large volumes of data to generate insights and actionable recommendations to drive business growth.
• Contributed to data mining architectures, modeling standards, reporting, and data analysis methodologies.
• Experience in Linear Programming, Quadratic Programming and Genetic Algorithm.

Experience in Statistical Modeling, Optimization, Data Mining, Machine learning techniques and algorithms, Cluster Analysis, Demand Forecasting, Python, Scikit Learn,Tensorflow.

• Responsible for implementing data mining and statistical machine learning solutions to various business problems.
• Analyze large volumes of data to generate insights and actionable recommendations to drive business growth.
• Contributed to data mining architectures, modeling standards, reporting, and data analysis methodologies.
• Experience in Linear Programming, Quadratic Programming and Genetic Algorithm.
• Experience in Statistical Modeling, Time Series Analysis, Optimization, Data Mining, Machine learning techniques and algorithms, Cluster Analysis, Demand Forecasting, R, SQL.

• Responsible for implementing data mining and statistical machine learning solutions to various business problems.
• Analyze large volumes of data to generate insights and actionable recommendations to drive business growth.
• Contributed to data mining architectures, modeling standards, reporting, and data analysis methodologies.
• Experience in Linear Programming, Quadratic Programming and Genetic Algorithm.
• Experience in Statistical Modeling, Time Series Analysis, Optimization, Data Mining, Machine learning techniques and algorithms, Cluster Analysis, Demand Forecasting, R, SQL.

• Creating SSIS packages to fetch the Data from Database to Data Warehouse.
• Deploying packages using project deployment and monitoring daily loads.
• Developing store procedures, triggers, views as an input to the reports.
• Creating scheduled jobs for the database to load data in the tables.