Mythri K

Project 1-> [ August 2017 - September 2019]

Project is about maintenance of one of the CRM Application on telecom domain where Customers are able to order the subscription and agreements for the mobile which is developed using the Java, GWT, Spring ,Spring MVC technology ,built using ANT and running with weblogic server.

• Experience in Python,C/C++, Basics of java ,plsql,GWT frame work(CRM Application and telecom domain)
• Successfully able to deliver the issues reported within the SLA’s given.
• Wrote Python scripts for daily maintenance activities, including indexes and tables analyses.
• Directed development across multifaceted team to meet client needs for functionality, timeline and performance.
• Worked in preparing package , Deployment of the package,Preparation of release notes.
• Partnered with development team on product development, application support plans, and prototype programs.

Project 2-> [ january 2020-september 2020 ]

Project is about maintenance of the routers ,assigning a new IP phones for the Customers using cisco communicator and monitoring the same with the mentioned privacy settings across the world.

• Successfully able to resolved the issues reported within the SLA’s given.
• Reviewed IP phones specifications and designed technology solutions that met or exceeded performance expectations.
• Actively listened to customers' requests, confirming full understanding before addressing concerns.
• Worked closely with Security and Networking team members to maintain optimum levels of communication to effectively and efficiently complete projects.

Medical Insurance premium predication analysis:Insurance is a policy that eliminates or decreases loss costs occurred by various risks. Various factors influence the cost of insurance. Different models of regression are used to forecast insurance costs. Data is trained on Different models [ Support Vector Machine, Decision tree,Random Forest Regressor, k-Nearest Neighbors] and the results are compared. The model obtained with RMSE value of 4054.and accuracy 86% in Radom forests regression.

Responsibilities:

• Exploratory Data Analysis
• Model building using different algorithms
• Performance Analysis