Master of Science in Public Policy Data Science

Program Director (Data Science): Yolanda Gil, PhD

Program Co-Director (Public Policy): T.J. McCarthy, PhD

The Master of Science in Public Policy Data Science is an interdisciplinary program offered jointly between the USC Sol Price School of Public Policy and the USC Viterbi School of Engineering.

This program blends fundamentals of data science with public policy and uniquely prepares students for careers in government agencies to leverage new data technologies to inform public policy decision making.  The increasing availability of data is revolutionizing the way many agencies operate, particularly with respect to governance transparency and accountability, law enforcement, transportation and housing policy.  This is causing profound changes in strategies for crime-fighting, defense, national intelligence, social programs, and finance and operations of agencies. The effective use of data science holds the potential to revolutionize how public policy is created.

The USC Master of Science in Data Analytics for Public Policy provides students with the knowledge and skills to:

  • Understand how big data can be used by governmental agencies to increase transparency and accountability, improve efficiency and performance of agencies and increase quality of services, handle emergency management, and better tackle issues of defense and intelligence.
  • Understand the institutional and legal challenges associated with collecting, combining, and analyzing ‘big-data’ from dispersed multiple sources relevant to inform and guide public policy decision making.
  • Understand how principles and capabilities of informatics, including mining and visualization of large datasets, can be relevant for public policy.
  • Understand how to incorporate predictive tools from data science, such as machine learning and data mining, with public policy and project evaluation methods that rely on causal inference, such as statistics and econometrics.

Students can pursue careers in a variety of sectors.  Many government agencies now have a dedicated data science and/or innovation unit, while several leading technology companies have created specialized divisions and products aimed at leveraging these tools in the public policy realm. Understanding and knowing how to use effectively data science is crucial for work in nongovernmental organizations and nonprofits as well.  Application areas for public policy data science include healthcare access, fair housing practices, crime pattern identification, and education financing.

The curriculum is designed to be accessible to students with any background, including students with a public policy background and no computer science knowledge as well as students with a computer science background and no public policy knowledge.  Students with undergraduate degrees in computer science, engineering, science or mathematics will acquire the necessary knowledge to analyze health data with diverse sources and purposes, and can request to replace introductory data science courses with more advanced ones.  Students with undergraduate degrees in public policy, political science, economics, and other social sciences will acquire formal and practical data science skills, and can request to substitute introductory courses in public policy with more advanced ones.  There is no requirement of prior knowledge of programming or computer science, as the curriculum is designed with special introductory courses that are accessible to students with diverse backgrounds.

Students complete a core set of courses to provide a foundation in data science and public policy, and choose electives to optimize their preparation for their preferred career path and unique professional opportunities. Students will learn a range of data science skills such as developing scalable data systems, using state-of-the-art software and infrastructure for data science, designing data analyses with statistical methods, applying machine learning and data mining techniques, designing effective visualizations, and working in multi-disciplinary data science teams. They will also learn the foundations of economics, cost-benefit analysis, and statistical and econometric methods should be coupled to effectively analyze public policy challenges, and inform and guide public policy decisions.  Through a capstone project, students will work in groups to produce a consulting-style report, which will demonstrate their capabilities and skills for the job market.

Throughout their course work, students will assemble a digital portfolio that will allow help them demonstrate their capabilities and skills for the job market.  Students will also have ample opportunities to be involved in practical public policy data science projects on campus.  Upon graduation, students will have both foundational and practical skills for a successful career in public policy data science.

A minimum of 32 units are required for completion of this degree.