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Graduate Overview

The world creates 2.5 quintillion bytes of data annually, and 90% of it has been produced in the last two years. This data revolution is fundamentally changing the kinds of skills the professional world is demanding of its workforce, but it also presents a host of ethical concerns related to bias, social responsibility, and privacy, which future data scientists must be prepared to address.

The Department of Quantitative Theory and Methods (QTM) offers a new STEM-designated, 15-month Master of Science (MS) designed to create researchers who consider the ways data can be used for social good. QTM MS curriculum will include the standard training in data management and predictive modeling; however, students will distinctively gain an education that combines the traditional study with research design, theory, causal inference, and technical communication. The program culminates with a capstone research project where students will have the opportunity to apply their knowledge, creativity, and experience to solve a real-world problem within their community.

Price Waterhouse Cooper’s (PWC) 2017 indicates that most of the workforce demand across a variety of professional sectors is for functional analysts and data-driven decision-makers, rather than pure data engineers. Students who complete the QTM MS will be poised to fill this key segment of the market through their intimate understanding of numbers, narrative, and nuance.