Client - Trizetto Roles and Responsibility: * Data Science proficient with 1+ years of involvement in conveying end to end information science ventures utilizing Python and Tableau. * Capability in measurements, machine learning and making convincing representations. * Worked in multiple parts for Retail, Banking and Insurance for better improvement. * Business understanding, Data understanding, Data planning, Modeling, Evaluation and Deployment. * Experience on Data wrangling, Data preparation and Data Visualization R and Tableau. * Significant expository and critical thinking aptitudes alongside capacity to comprehend current business forms and execute successful solution. * Worked with different business units within sales and marketing to understand information needs and provide effective data management and analysis solutions to analyze business environment. * Turned out to be interested to mine shrouded bits of knowledge and present complex information examination to non-systematic group of onlookers. * Implemented surveys, interviews and expert meetings to identify client demand and key challenges.
* Skills: Data Visualization, Data Manipulation, Statistical Analysis and Machine Learning * Tools: Tableau * Programming Languages: python
Classifying the customers based on location, type of compliant, severity of the compliant with automation based on SVM
* Collected 100000 Customers Data, we are having 10 Different Customer Types. * To make automated, we implemented SVM with Radial based Kernel * Trained on 80,000 Rows on 12 different features and tested on 20,000 rows. We got an accuracy of 80% when we used Linear Kernel * To improve the accuracy of the model, we used radial based kernel and achieved an accuracy of 91.53%
Failure of Encoder Component:
* Before a scanner going to fail we need to predict the survival gap of the scanner. To model this problem we collected 1lakh rows to understand failure rate of each and every individual scanner. * We modeled Failure rate of the scanner based on other parameters which are right indicator to predict the survival gap. * We had various discussions with the concerned team related to scanners and extracted best features to build this model. * We future engineered and pick best features based on decision tree. * Build this model on top Random Forest Algorithm with an accuracy 98%.
CMC India Private LimitedDecember 2009 - September 2010
Roles & Responsibility:
* Testing the Functionality as per TATA -CMC Testing Standards. * Writing and Executing the Test Cases. * Finding the bugs and isolating the bugs. * Reporting defects in defect Tracking System (BUGZILLA)
Hadoop, Hive, Spark
Manual testing, Automated testing, Test Cases
Analysis methods and tools
Bugzilla, Agile Methodology
Analytics, Data processing
industry~it, a key advisor, Functional Tester, analytics project management experience, Cluster Analysis, effective data management and analysis, Bachelors Degree > Bachelor of Technology > Bachelor of Technology Electrical and Electronics Engineering, Defect Management, Python Programming, TATA -CMC Testing, Data Visualization, Data Manipulation, Statistical Analysis, Mathematical Modelling > Statistical Modelling, Data Scientist, Post modelling analysis, tableau, LSI StoreAge > StoreAge SVM, Critical Thinking, Scrum Methodology, Data planning
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