Aivin Solatorio is a data scientist with the World Bank's Development Data Group. He specializes in applying machine learning and AI techniques to solve economic development and operational problems. He has worked on a myriad of projects including the application of machine learning in the areas of climate change, logistics, digital sectors, digital skills in labor markets of developing countries, and poverty prediction research. He is also experienced in building agent-based models (ABM) to simulate real-world scenarios for policy making and has worked on processing and analysis of massive smartphone GPS location dataset to develop risk indicators of mobility during the CoVid-19 pandemic. His primary interest is building machine learning, information retrieval, and natural language processing (NLP) applications for the discoverability of various development economic data ranging from project and research documents and microdata. Aivin holds a master's degree in Physics from the University of the Philippines.