Essential interpersonal skills are becoming increasingly common in the job postings for data science positions. Cross-functional employee management skills are one of the keys to running a successful big data project. Managing your big data project will likely put you into contact with new departments and technical/business specialties. While big data project managers need the work product of many other departments, they are rarely given control over these other departments. The Management Sciences pathway provides you with the tools you will need to motivate and direct the work of others even when they do not report to you.
The courses in this pathway cover key management skills such as managing teams and projects and strategic and financial management.
Prerequisites
Admission into the Data Science graduate program.
Courses
Students learn the fundamentals of managing projects in a systematic way. These fundamentals can be applied within any industry and work environment and will serve as the foundation for more specialized project management study. Principles and techniques are further reinforced through practical case studies and team projects in which students simulate project management processes and techniques.
Students analyze leadership case studies across a wide range of industries and environments to identify effective leadership principles that may be applied in their own organizations. Students learn how to influence people throughout their organization, lead effective teams, create an inclusive workplace, use the Six Sigma process, implement and manage change and develop a leadership style.
Prerequisite: ENMG 652: Management, Leadership and Communication
This course focuses on analysis and interpretation of financial statements with an emphasis on measuring the results of operations and financial position of business organizations. Course topics include: compilation of financial statements, ratio analysis, business profitability- breakeven analysis, return on assets, return on investment, business financing, planning and budgeting.
This course is intended to integrate the learning from the previous engineering management courses and to focus it on the perspective and problems of the Chief Executive Officer and other “C-suite” organizational strategic managers. The focus is on understanding the Strategic Management Process (SMP) in large organizations, which includes both strategy formulation and strategy implementation. There is a particular focus on strategic management of technology and innovation. The theme of the course is that large organizations do better when they formulate a strategic action plan based on their strategic management process. In addition to case studies and textbook readings, working in groups, students will complete a Business Plan to develop and demonstrate their strategic management skills.
This course is designed to help the student apply managerial concepts and skills to managing and leading virtual and/or global work teams. Geographically dispersed work teams have great challenges: tone is difficult to convey electronically, time zones limit audio communication opportunities, work oversight requires more reposting, and team building is exceedingly difficult using technological – rather than in-person – tools. Language and culture differences in multinational teams compound these challenges. Students will learn to empower others, build credibility, communicate appropriately and adapt quickly across cultures and technologies.
This advanced course in project management builds on the beginner level project management courses to expand the hands-on applications, with a focus on critical evaluation of project performance and ultimately creating an environment for maximizing one’s own project management performance. With a strong emphasis on the importance of learning through application, the course will bridge academia with the professional business environment to provide opportunities for students to interact with industry professionals as the students execute their course work. Students will also confront the real challenges facing project managers associated with the growing global and virtual workforce through the use of online learning tools and methods of collaboration. At the successful completion of the course, students will have the requisite skills and experiences necessary to function effectively, and artfully, as skilled project managers.
This course provides an overview of the basic principles and tools of quality and their applications from an engineering perspective. The primary quality schools of thought or methodologies, including Total Quality Management, Six Sigma and Lean Six Sigma, and quality approaches from key figures in the development and application of quality as a business practice, including W. Edwards Deming and Joseph M. Juran will be analyzed. Some of the key mathematical tools used in quality systems will be discussed, including Pareto charts, measurement systems analysis, design of experiments, response surface methodology, and statistical process control. Students will apply these techniques to solve engineering problems using the R software. Reading assignments, homework, exams, and the project will emphasize quality approaches, techniques, and problem solving.
This course will cover fundamental project control and systems engineering management concepts, including how to plan, set up cost accounts, bid, staff and execute a project from a project control perspective. It provides an understanding of the critical relations and interconnections between project management and systems engineering management. It is designed to address how systems engineering management supports traditional program management activities to break down complex programs into manageable and assignable tasks.
This course explores the best management practices of international projects, emphasizing the importance of leadership skills and virtual teamwork to successfully navigate through managing an international project. International projects differ from domestic projects by their complexity of culture, increased communications and collaboration requirements, local customs and practices, differing languages and currencies, processes, and the type of resources that may be available. The course describes how to conduct project planning in each of the life cycle acquisition process phases and then to execute the plan through recommended international organizational structures.
This course provides an overview of decision and risk analysis techniques. It focuses on how to make rational decisions in the presence of uncertainty and conflicting objectives. This course covers rational decision-making principles and processes; competing objectives, multi-attribute analysis and utility theory; modeling uncertainty and decision problems using decision trees and influence diagrams; solving decision trees and influence diagrams; uses of Bayes’ Theorem; defining and calculating the value of information; regression analysis; incorporating risk attitudes into decision analyses; and conducting sensitivity analyses. A significant portion of the course is devoted to the use of various applications of analytic, empirical, and subjective probability theory to the modeling of uncertain events. As such, students will find it useful to have some experience with basic probability.
This course can be counted as either a management course or an engineering course for the M.S. in Engineering Management.
The special topics course explores current topics in Systems Engineering.
Career Outlook
A skilled data scientist that possess strong management skills is an essential employee. According to Labor Insight, an employer-demand tool, the top skills required in job postings for data science positions include decision making, planning, communications, and project planning.
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