Arya Harilal
About Arya Harilal
Arya Harilal is a Research Engineer at Soul Machines in Auckland, New Zealand, with a diverse educational background in business analytics, information systems, computer science, and psychology. She has contributed to various systems and data engineering projects and has previous experience as a consultant and intern in the technology sector.
Work at Soul Machines
Arya Harilal currently serves as a Research Engineer at Soul Machines, a position held since 2022. In this role, he contributes to systems and data engineering projects, leveraging his expertise to enhance the company's technological capabilities. Prior to his current role, he was an R&D Intern at Soul Machines for three months in 2021, where he gained valuable experience in research and development within the organization.
Education and Expertise
Arya Harilal completed his studies at The University of Auckland, earning a BCom/BSc degree from 2017 to 2021. His educational background encompasses business analytics, information systems, computer science, and psychology. This diverse academic foundation equips him with a unique perspective on system improvement and innovation. Additionally, he studied at Macleans College, where he achieved Cambridge International AS and A Levels from 2012 to 2016.
Background
Before joining Soul Machines, Arya Harilal worked as a Consultant at Fonterra in 2020 for 11 months. He also volunteered as a Student Volunteer at Robogals Auckland in 2019 for 11 months, where he engaged in initiatives aimed at promoting engineering among young women. His varied experiences contribute to his strong interest in improving and innovating systems and processes.
Professional Experience
Arya Harilal has accumulated diverse professional experience in various roles. His tenure at Fonterra as a Consultant involved applying his analytical skills to real-world challenges. His earlier role as an R&D Intern at Soul Machines allowed him to immerse himself in research and development, further enhancing his technical skills and understanding of data engineering.