Data Scientist at IBM Chief Analytics Office, Researcher at MIT-IBM AI Lab
Tin Oreskovic is a Data Scientist at IBM’s Chief Analytics Office, and a Researcher at an MIT-IBM AI Lab's project focusing on developing models that infer the causal effects of opioid usage on individuals and predict adverse outcomes. He is also involved in several other empirical research projects, including a multisite randomzied controlled non-inferiority trial comparing two smoking cessation drugs (Harvard Medical School, MGH, Faculty of Medicine Ljubljana, Zagreb); and an examination of the gender wage gap among Boston City's employees. He is a Brown University graduate in Econometrics and Quantitative Economics as well as in Philosophy, and a Columbia University graduate in Data Science.
In 2018, Tin initiated a University of Chicago Data Science for Social Good project to develop a predictive model of vaccination outcomes, and coordinated the work of a data science team with that of public health officials and medical doctors. He believes that despite the numerous challenges, there are great opportunities to apply data science methods for impact in public policy and the social sector.
Tin received several prizes, including the Ducasse Prize for Excellence in Philosophy and the Data Science for Social Good Europe Champion award. Before joining IBM, he worked on a Microsoft Research project in partnership with Columbia's Data Science Institute aiming to forecast congressional election outcomes using non-representative online polling processed by multilevel modeling and poststratification, and to compare the benefits of asking generic ballot vs. candidate-specific questions.