Subhajit Saha

· Third Space:

Senior Node.Js Developer

Technology: Node.js, express js, PostgreSql, React.js, AWS, sequelize

In this project I'm currently working as node.js developer. Developed common libaries which will be used by all the microservices. Developing COS related api's using which we can upload, download ,delete any kind of file from AWS S3 bucket.

· Haven:

Full stack Developer

Technology: Node.js, express js, PostgreSql, React.js, AWS, sequelize

In this project I have worked as full stack developer. As a part of backend team I have not only developed api's also worked as module lead of two microservices, some of the nodejs packages which I have used to develop api's jsonwebtoken, joi,bcryptjs etc. Used sequelize to store, fetch and modify date in PostgreSql. As a part of frontend team used Html, Css, Reactjs to develop UI.

· HDC Project:

Senior Node.Js Developer

Technology: Node.js, MongoDB, AWS

In this project as a part of backend development team I have developed have api’s for an educational app using node.js . I have written code to established connectivity between backend api’s and mongo DB and written queries to store, fetch and modify date in Mongo DB. We have deployed our api in AWS.

· ID-Mobile:

Node.Js Developer

Technology : Node.js, MongoDB, Python

In this project Iwas part of both backend team and data science team. This is a telecom project, as part of backend team we have developed api’s and as part of data science team we have build model to predict the customer’s those have high chances to switch to another telecom service providers. This has helped client to improve and also to adopt policies which can stop customer from switching to another telecom service provider.

· Xcel Energy:

Technology: Machine Learning, Deep Learning, NLP, Python, Flask

In this project I have worked as Data Scientist to build a ML/DL model to automate process in Tech Support Team that can manage ticket/case raised by users for getting support, without any human intervention. System will assign ticket to the corresponding responsible team, set the correct Label by processing text Summary and Description mentioned in the ticket by NLP and ML/DL algorithm. This will results support team’s function automatic, faster and error less and need of less man resource, ultimately saving cost.