Rajapreethi Rajendran

is about to graduate. 🎓

Angestellt, Working Student Web Application developer, exocad GmbH

Student, High Integrity Systems (Computer Science and Data Science), Frankfurt University of Applied Sciences

Frankfurt am Main, Deutschland

Über mich

I am a software engineer with over six years of work experience in full-stack development. I am pursuing a Master's in High Integrity Systems which focuses on Computer Science and Data Science, I bring a solid foundation of theoretical knowledge and practical expertise to my work. I am open to a role in software development/data science/ data analytics/ data engineering/ business intelligence

Fähigkeiten und Kenntnisse

Software
Engineering
Java
Python
Technology
Project Management
Software Development
Infrastructure
Information technology
Agile Development
.NET
Data Science
Data Analysis
SQL
VAADIN
Business Intelligence
FinTech
Management
Team collaboration
Agile Software Development
Machine Learning
Database
Programming Language
Web applications
Spring Framework
Software framework
Maven
Gradle
Vaadin
Docker
Full-stack development
PostgreSQL
API

Werdegang

Berufserfahrung von Rajapreethi Rajendran

  • Bis heute 2 Jahre und 2 Monate, seit Mai 2022

    Working Student Web Application developer

    exocad GmbH

    Project: Bug Report Analysis Tool -Actively developing a Java web application utilizing the Vaadin framework for a Bug Report Analysis Tool. -Dockerized the application to streamline deployment and enhance management efficiency. -Implemented updates to both Vaadin and Java, capitalizing on the latest features for improved functionality. -Integrated enhancements to elevate application performance and user experience. -Employed Hibernate/JPA ORM for efficient database interactions and management.

  • 4 Jahre und 6 Monate, Apr. 2017 - Sep. 2021

    Associate Technical Lead/Senior Software Developer/Software Developer

    Odessa inc

Ausbildung von Rajapreethi Rajendran

  • Bis heute 10 Monate, seit Sep. 2023

    Master Thesis Student at Frankfurt University of Applied Sciences

    Frankfurt University of Applied Sciences

    Forecasting Glass Trash Collection Using Machine Learning The project focuses on enhancing the efficiency of glass waste collection in a German city by leveraging historical data. To achieve this optimization, the proposed solution involves the development of a machine-learning model. The ultimate goal is to streamline the waste collection process through accurate forecasting based on insightful data analysis.

  • Bis heute 2 Jahre und 9 Monate, seit Okt. 2021

    High Integrity Systems (Computer Science and Data Science)

    Frankfurt University of Applied Sciences

  • 3 Jahre und 11 Monate, Mai 2013 - März 2017

    Electronics and Communication Engineering

    Anna University, Chennai

Sprachen

  • Englisch

    Fließend

  • Deutsch

    Grundlagen

  • tamil

    Muttersprache

Interessen

Cooking

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