Claudia Perlich joined Two Sigma as SVP of Strategic Data Science after leaving Dstillery, where she served as a chief scientist (2010 to 2017). In this role, she was responsible for the reliable estimation of targeting models (predictive modeling/ranking models using NB/logistic regression and others), the performance evaluation of systems/models and campaigns both in vitro and vivo, as well as the supervision of a real-time scoring engine that applies the models to identify the target segments of browsers. Since 2011, Claudia has also worked as an adjunct professor teaching Data Mining in the M.B.A. program at the New York University Stern School of Business. As a research staff member in the Data Analytics Research Group at the IBM Watson Research Center (2004 to 2010), she led teams that completed successfully in KDD Data Mining Competitions, designed and executed wallet/opportunity estimation models for IBM Sales using quantile regression, and worked on blog and twitter analysis tools for marketing. Claudia holds a Ph.D. in Information Systems from the New York University Stern School of Business (2004), an M.S. in Computer Science from Technical University Darmstadt, Germany (1998), an M.S. in Computer Science from the University of Colorado (1996), and a B.S. in Computer Science from Technical University Darmstadt, Germany (1995).