Pavithra Vijayan
About Pavithra Vijayan
Pavithra Vijayan is an Application Developer Engineer specializing in machine learning at Arista Networks and a book author at Become Data Scientist. She has extensive experience in software engineering and data analysis, with a background in Information Technology.
Company
Pavithra Vijayan is currently employed at Arista Networks as an Application Developer Engineer in the field of Machine Learning. She has been with Arista Networks since 2021, based in Bangalore Urban, Karnataka, India. Her role involves working on projects that leverage machine learning technologies.
Role at Become Data Scientist
Pavithra Vijayan also serves as a Book Author at Become Data Scientist. She started this role in 2020 and is based out of Vellore, Tamil Nadu, India. Her work involves authoring content related to data science, aiming to provide resources and knowledge to aspiring data scientists.
Previous Experience at EXL
Before joining Arista Networks, Pavithra worked at EXL as a Healthcare Data Analyst from 2019 to 2021. During her tenure in the Chennai Area, India, she was responsible for analyzing healthcare data and providing insights that could drive business decisions.
Previous Experience at HCL Technologies
Pavithra Vijayan has extensive experience with HCL Technologies. She served as a Software Engineer from 2017 to 2019 in Chennai, Tamil Nadu, and handled end-to-end development of machine learning projects, including core software engineering tasks. Before this, she was a Management Intern at HCL Technologies from 2016 to 2017. At HCL, she worked on projects like Automatic Speech Recognition and Auto Punctuations using Deep Neural Networks.
Education and Expertise
Pavithra Vijayan pursued her academic qualifications at two reputable institutions. She earned her M.Tech degree in Information Technology from the Vellore Institute of Technology between 2015 and 2017. Prior to that, she completed her Bachelor's degree in Information Technology from Ganadipathy Tulsi's Jain Engineering College, from 2011 to 2015. During her Master's degree, she gained practical experience in dealing with large-scale data, focusing on machine learning models for business and optimization problems.