Iavor Bojinov is an Assistant Professor of Business Administration in the Technology and Operations Management unit at Harvard Business School and a faculty affiliate in the Department of Statistics at Harvard University. He teaches the first-year Technology and Operations Management course. Previously he has led multiple data science courses and regularly guest lectures on a diverse set of topics ranging from experimentation to machine learning. Professor Bojinov’s research interest is at the interface of causal inference, experimental design, and large-scale computing with the overall goal of democratizing statistical methods in order to help firms innovate and grow. Currently, he is actively pursuing three related research areas: design and analysis of experiments in complex settings, demystifying the value and limitation of experimentation, and understanding the role of data science in the modern AI organization. His work has been featured in top Statistics journals such as Biometrika and the Journal of the American Statistical Association. More broadly, as one of the few scholars that work at the intersection of data science and business, he was the first author to have spotlight featured articles in both the Harvard Business Review and the Harvard Data Science Review. Before joining Harvard Business School, Professor Bojinov worked as a data scientist leading the causal inference effort within the Applied Research Group at LinkedIn. He holds a Ph.D. and an MA in Statistics from Harvard and an MSci in Mathematics from King’s College London.