Vivek Kumar is a Python Developer with 6+ years of experience in building scalable applications and integrating complex systems. He has a strong background in cloud technologies and machine learning.
Successfully transformed a PyQt5 desktop scientific tool into a web application.
Developed and maintained core rating microservices for an insurance platform.
Implemented a machine learning solution for parsing patient PDF documents.
Built and managed multiple Vue.js-based portals and Django backend APIs.
Developed rating microservices critical for insurance premium calculations, impacting accuracy by 30%.
Transformed a scientific tool into a web application, increasing user accessibility by 50%.
Implemented a machine learning solution that reduced document processing time by 40%.
Overview: Innovisk is a U.S.A.-based company providing 3rd party insurance to its customers. Responsibilities: Developed and refactored Rating microservices for the Insurance-based model, implementing business logic related to client requirements. Created algorithms to calculate insurance premiums based on various U.S. states.
Key outcomes:
Developed rating microservices critical for insurance premium calculations, enhancing system accuracy.
Overview: ARED is an AI-powered distributed infrastructure-as-a-service company, providing smart WiFi management solutions. Responsibilities: Developed the Captive Portal using PHP and Python for customer logins via voucher or QR codes. Built and maintained SME, Partner, Devices, and Admin portals using Vue.js for various user roles and device management. Implemented the backend API using Django framework and integrated authentication systems.
Key outcomes:
Contributed to the development of a comprehensive smart WiFi management solution for diverse clients.
Integrated multiple backend systems and frontend portals for a unified service offering.
Overview: This project involved transforming a scientific tool developed in PyQt5 into a web application. Responsibilities: Created the ontology and equations for the application, saving all data in JSON format. Developed a linker to create new variants of network nodes based on equations and behaviors.
Key outcomes:
Successfully converted a desktop PyQt5 scientific tool into a web-based application.
Overview: A machine learning project designed to read data from patient PDF documents and generate conclusions for doctors. Responsibilities: Utilized PyPDF2, TensorFlow, scikit-learn, and Pytesseract to extract text from PDF files.
Key outcomes:
Developed an ML solution for automating the extraction and interpretation of medical data from PDFs.
Vivek Arya
Python Developer