Dr. Iris Malone is a trained data scientist and geopolitical analyst. They have experience designing, evaluating, and deploying quantitative models to measure geopolitical risks using supervised machine learning methods. They have taught courses in data science, econometrics, and conflict analysis. Iris has also published on conflict forecasting and political economy issues in peer-reviewed journals and textbooks. Quantitative Methods: Statistics (probability theory, regression, ridge, lasso, multilevel modeling, biostatistics, nonlinear models, bayesian, markov), econometrics (causal inference, survey design, forecasting), machine learning (principal component analysis, factor analysis, cluster analysis, decision trees, random forests, boosting, support vector machines), deep learning (recurrent neural nets, convolutional neural nets, gan, lstm, tensorflow), text analysis (natural language processing, topic modeling, document classification, sentiment analysis), data science (collection, cleaning, analysis, visualization) Qualitative Methods: Case studies, interviews, archival research, deep web researchTechnical: R, Python, SQL, STATA, GIS, HTML, Microsoft Excel, Microsoft Powerpoint, Tableau