Sudharsan Sridharan
About Sudharsan Sridharan
Sudharsan Sridharan is a Data Analyst at LatentView Analytics in Chennai, India, with a B.Tech. in Mechanical Engineering from Shanmugha Arts, Science, Technology and Research Academy. He has a strong interest in supply chain management and possesses skills in data visualization and analysis.
Work at LatentView Analytics
Sudharsan Sridharan has been employed as a Data Analyst at LatentView Analytics since 2020. He has accumulated four years of experience in this role, contributing to various projects and initiatives within the company. His work focuses on data analysis, where he applies his skills to interpret and present data effectively.
Education and Expertise
Sudharsan completed his B.Tech. in Mechanical Engineering at Shanmugha Arts, Science, Technology and Research Academy from 2016 to 2020. Prior to this, he attended Ashram Matriculation Higher Secondary School for his early education from 2003 to 2008 and later studied at Modern Senior Secondary School in Nanganallur, Chennai, from 2009 to 2016. His academic background provides a foundation for his analytical skills and interests.
Background
Sudharsan Sridharan has a diverse educational background, having attended multiple institutions in Tamil Nadu, India. His early education spanned from 2003 to 2016, culminating in a degree in Mechanical Engineering. This educational journey has equipped him with a strong technical foundation that supports his current role in data analysis.
Leadership Experience
Sudharsan served as the Head of Team Public Relations at Daksh Techno-management fest. In this role, he demonstrated leadership and communication skills, managing a team and engaging with various stakeholders. This experience highlights his ability to lead and coordinate effectively in a team environment.
Interests in Supply Chain Management
Sudharsan has a keen interest in supply chain management, focusing on optimizing processes and enhancing efficiency. This interest aligns with his analytical skills and may influence his approach to data analysis, particularly in areas related to logistics and operational improvements.