Sidharth Rony is Post-Doctorate Researcher at UNU-MERIT from January 2024
Sidharth Rony is a researcher in computational social science, specializing in the intersection of education, technology, and labor economics. Currently finishing his PhD in Economics at Royal Holloway, University of London, he leverages machine learning techniques to explore complex economic questions. His research interests include the impact of automation on the future of skills in the labor market, measurement of skill and wage premier from job advertisements.
Sidharth's academic background is extensive, holding an MSc in Economics and Financial Research from Maastricht University, where his thesis explored signaling asymmetric information in auctions. He also completed doctoral coursework in the Economics of Education at the University of Zurich. His earlier training includes a BTech in Electronics and Communication Engineering from Amrita Vishwa Vidhyapeetham, demonstrating a diverse skill set.
His professional experience is encompassing research, teaching, and consulting roles. He has served as a Research Assistant at the London School of Economics (LSE), assisting the policy evaluation team at the What Works Centre for Local Economic Growth. He has also held teaching positions at Royal Holloway, instructing students in econometrics, data skills, and coding. Sidharth has contributed to research projects at Royal Holloway, including an investigation into the impact of public-sector employment on private-sector job creation in Ghana, involving collaboration with government institutions. He has also consulted for the OECD, analyzing job postings data, and worked as a Research Associate at the Centre for Development Studies in India, leading data collection efforts for a large-scale migration survey.
Sidharth is an Office of National Statistics (ONS) Accredited Researcher and an Associate Fellow of the Higher Education Academy (AFHEA). His research has been recognized through awards and grants, including an Economic and Social Research Council (ESRC) studentship. He actively engages in further training, having completed advanced courses in economic fitness and complexity, applied microeconomics, and machine learning. He looks forward to contributing to cutting-edge research and collaborating with a diverse team of economists, data scientists, and innovation scholars.