Nandani Kumari Roma
About Nandani Kumari Roma
Nandani Kumari Roma is an Associate Software Engineer at Innoplexus, specializing in data analytics and software development. She holds a Master of Science in Signal Processing from the Indian Institute of Technology, Kanpur, and a Bachelor's Degree in Electrical Engineering from Sardar Vallabhbhai National Institute of Technology, Surat.
Work at Innoplexus
Nandani Kumari Roma has been employed at Innoplexus as an Associate Software Engineer since 2020. In this role, she addresses ad hoc analytics requests and facilitates data acquisitions through web crawling techniques. Her responsibilities also include coordinating the deployment of new mobile applications, which encompasses feature updates and fixes. Additionally, she has experience in automating the extraction, transformation, and loading of data within production pipelines.
Education and Expertise
Nandani Kumari Roma holds a Master of Science (MS) in Signal Processing from the Indian Institute of Technology, Kanpur, where she studied from 2017 to 2020. Prior to this, she earned a Bachelor's Degree in Electrical Engineering from Sardar Vallabhbhai National Institute of Technology, Surat, from 2008 to 2012. Her academic background provides her with a strong foundation in engineering principles and data processing techniques.
Background
Nandani Kumari Roma began her career at ESSAR PROJECTS (INDIA) LIMITED, where she worked as an Assistant Manager from 2012 to 2014 in the Mumbai Area. Following this, she served as a Project Associate at the Indian Institute of Technology, Kanpur, for 11 months in 2016. These roles contributed to her experience in project management and technical development.
Technical Skills and Projects
Nandani Kumari Roma has developed a range of technical skills throughout her career. She has revised, modularized, and updated old code bases to meet modern development standards, which has led to reduced operating costs and improved functionality. Additionally, she has worked on feature engineering of non-English texts using the NLTK library, achieving over 60% accuracy in her projects.