SANJITH SENNIANGIRI

• Worked on 20+ projects specific to STS application and 5+ projects specific to SCPAY application built using Java Spring Framework.

• Added a Database-based approach to the application to restrict frequent modification of core and generic framework.

• Worked and supported in code deployment to production, raising PTP’s and other devops activities even during weekends.

• Experienced in working with PL/SQL and writing related procedures.

• Worked on creating 5 new microservices for SCPAY application and promoted them to production.

• Assisted trainees with their projects and guided them by providing several KT sessions.

• Worked with Business Analyst to get the requirements from client, understood the scope of change, did impact assessment and delivered the change.

• Supported other teams as SPOC (Single Point of Contact) and SME (Subject Matter Expert) for my team.

• Experience in working with Jenkins, Kibana, and OCP.

• Attended the fresher's boot camp and worked in STS (Straight Through Services) application built using Java microservices .
• Experienced in Banking Sector (IT).
• Experienced/Worked in teams following Agile Methodology (Scrum Team).
• Worked in CCIB Domain (Corporate Commercial and Institutional Banking).
• Worked as a developer on 15+ java projects as a part of RAD (Rapid Application Development) team using Java, SQL Developer, XML, GIT etc.
• Developed and deployed all the projects along with the technical documents preparation.
• Also, experienced in working with Jira, Confluence, GIT, BitBucket, WinSCP, Putty/MTPutty, etc.

• Developed the 'Credit Card Origination' (full-stack) project that focuses on three types of users : Customer, Sales User and Checker User.
• The customer/sales/checker user pages were developed using HTML, Bootstrap, CSS, JavaScript.
• The customer applies for a credit card according to his interest. The Sales User gets the data from the Customer Portal and records it in the Database.
• Worked on Rest API's to fetch and store the customer's data to the DB(PostgreSQL) in the form of .JSON.
• The Checker User verifies the customer and passes the control to the Sales User.
• Now, the Sales User will verify the eligibility of the customer based on his CIBIL score and accepts or rejects the application.
• Got the 'Best Project' and 'Best Class' Award.
• Got the 'Best Performer' Award for resolute and excellent performance in overall training.

• Worked on the 'Expression Finder' project.
• Expression finder performs the task of classifying the expression on face images into various categories such as anger, fear, surprise, sadness, happiness, disgust and normal.
• Used the concept of CNN (Convolution Neural networks) to train the model with the data sets and improve the accuracy of the model.
• Used various libraries such as Keras, OpenCV, Pandas, Numpy etc.
• Used the following CNN layers for training the dataset and predicting/classifying the expression : Convolution, Pooling, ReLu, Fully Connected.
• This model can be used for prediction of expressions of still as well as real-time images. [PYTHON]