ACCELERATE YOUR CAREER TRAJECTORY TO BECOME AN ENGINEERING MANAGER

ONLINE MASTER OF ENGINEERING IN ENGINEERING MANAGEMENT

Recognized as the No. 9 Online Master’s in Engineering Management in 2022 by U.S. News & World Report.

ENGINEERING MANAGEMENT OVERVIEW

The Online Master of Engineering in Engineering Management (MEM) provides students with a strong understanding of how to create, manage and apply technology to engineering projects. Students build their expertise in both technical disciplines and people management through a holistic learning approach, and bring value to their respective enterprises. As an Engineering Management student, you will hone the skills you need to:

Leverage advanced techniques and analysis to estimate and use cost information in decision making.

Form and manage an effective engineering design team in a business environment.

Handle and process information using Python. 

Master the fundamentals of system dynamics and build system dynamic models.

QUICK FACTS

NEXT START DATE

January 23, 2023

OVERVIEW

  • 30 Credit Hours
  • 10 Courses
  • 100% Online
  • 2 Years or Less Average Completion Time*

*Total time to complete the program may vary based on the number of credits taken each semester.

No. 9

IN THE NATION

Recognized as the No. 9 Online Master’s in Engineering Management in the country by U.S. News & World Report (2022).

No. 14

IN THE U.S.

Ranked among the “Best Value Colleges” for  20-year return on investment by Payscale (2021).* 

No. 13

IN THE NATION

Recognized as one of the Top 20 U.S. Private Schools for Best Career Placement by The Princeton Review (2022).

100%

EMPLOYMENT

100% of MEM graduates in the Class of 2021 accepted job offers within three months of graduating.**

No. 1

IN N.J.

Named the No. 1 Online Master’s in Engineering Program at a N.J. school (U.S. News & World Report, 2022).

*Based on the cost of a four-year bachelor’s degree program.

**Based on data from 63% of spring 2021 graduates who attended full time.

COURSEWORK

Online Master of Engineering in Engineering Management students take coursework to build proficiency in the leading engineering technology and management techniques. Students choose between two program concentrations: Managerial Analytics or Supply Chain and Logistics Management.*

TERM 1

This course presents advanced techniques and analysis designed to permit managers to estimate and use cost information in decision making. Topics include: historical overview of the management accounting process, statistical cost estimation, cost allocation, and uses of cost information in evaluating decisions about pricing, quality, manufacturing processes (e.g., JIT, CIM), investments in new technologies, investment centers, the selection process for capital investments, both tangible and intangible, and how this process is structured and constrained by the time value of money, the source of funds, market demand, and competitive position.

This project-based course exposes students to tools and methodologies useful for forming and managing an effective engineering design team in a business environment. Topics covered will include personality profiles for creating teams with balanced diversity; computational tools for project coordination and management; real-time electronic documentation as a critical design process variable; and methods for refining project requirements to ensure that the team addresses the right problem with the right solution.

TERM 2

This course brings a strong modeling orientation to bear on the process of obtaining and utilizing resources to produce and deliver useful goods and services so as to meet the goals of the organization. Decision-oriented models such as linear programming, inventory control, and forecasting are discussed and then implemented utilizing spreadsheets and other commercial software. A review of the fundamentals of statistical analysis oriented toward business problems will also be conducted.

This course enables the engineering management student to acquire the knowledge and skills they will need to handle the variety and volume of information encountered in today’s workplace. The course uses Python, which is rapidly becoming the language of choice for information handling and data analysis. Students will work with both structured and semi-structured data.

TERM 3

This course emphasizes the development of modeling and simulation concepts and analysis skills necessary to design, program, implement, and use computers to solve complex systems/product analysis problems. The key emphasis is on problem formulation, model building, data analysis, solution techniques, and evaluation of alternative designs/ processes in complex systems/products. An overview of modeling techniques and methods used in decision analysis, including Monte Carlo and discrete event simulation is presented.

This course is a study of analytic techniques for rational decision-making that addresses uncertainty, conflicting objectives, and risk attitudes. This course covers modeling uncertainty; rational decision-making principles; representing decision problems with value trees, decision trees, and influence diagrams; solving value hierarchies; defining and calculating the value of information; incorporating risk attitudes into the analysis; and conducting sensitivity analyses.

TERM 4

Project success depends, largely, on the human side. Success in motivating project workers, organizing and leading project teams, communication and sharing information, and conflict resolution, are just a few areas that are critical for project success. However, being primarily technical people, many project managers tend to neglect these “soft” issues, assuming they are less important or that they should be addressed by direct functional managers. The purpose of this course is to increase awareness of project managers to the critical issues of managing people and to present some of the theories and practices of leading project workers and teams.

MANAGERIAL ANALYTICS ELECTIVES

This course provides a hands-on introduction to the modern techniques for visualizing data and leverages such techniques with the corresponding problem solving skills necessary to complement data visualization into specific strategic decision making. The student will first learn to use the latest off the shelf software for data visualization. In specific the student will learn the following languages: R, D3, Google refine and Spot fire.

SUPPLY CHAIN AND LOGISTICS MANAGEMENT ELECTIVES

The supportability of a system can be defined as the ability of the system to be supported in a cost effective and timely manner, with a minimum of logistics support resources. The required resources might include test and support equipment, trained maintenance personnel, spare and repair parts, technical documentation and special facilities. For large complex systems, supportability considerations may be significant and often have a major impact upon life-cycle cost. It is therefore particularly important that these considerations be included early during the system design trade studies and design decision-making.

TERM 5**

MANAGERIAL ANALYTICS ELECTIVES

Getting usable information from the vast amount of data we are immersed into requires a combination of methodologies, tools, techniques, algorithms and ingenuity. Creating views, extracting trends, defining patterns, identifying clusters are all elements we need to manage large data. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. Final goal of the course is to provide the students with a “data toolbox” they can use in their activities. This “toolbox” contains methods and tools that students will use themselves during the course for real world applications. The course is hand-on, but no coding is required, using Open Source Data Science tools that are based on Graphical User Interfaces.

SUPPLY CHAIN AND LOGISTICS MANAGEMENT ELECTIVES

This course covers the theory and application of modeling aggregate demand, fragmented demand and consumer behavior using statistical methods for analysis and forecasting for facilities, services and products. It also aims to provide students with both the conceptual basis and tools necessary to conduct market segmentation studies, defining and identifying criteria for effective segmentation, along with techniques for simultaneous profiling of segments and models for dynamic segmentation. All of this provides a window on the external environment, thereby contributing input and context to product, process and systems design decisions and their ongoing management.

The Capstone is a customized and personalized experience that allows students the opportunity to build innovative solutions for real-world engineering problems. Students will collaborate with a faculty member and tailor their projects to their areas of interest or use real-life issues at their current organizations.

*Applicants are not required to select a program concentration during the application process.

**Students lacking sufficient statistics coursework in their academic background will be required to take Probability and Statistics for Systems Engineering in lieu of an elective course. Once enrolled, students will work with a student support coach to determine which courses to take.

CAREER OUTLOOK

Graduates of the M.Eng. in Engineering Management program bring a blend of interpersonal and technical skills to a variety of engineering and engineering leadership roles.

Prospective Occupations for Engineering Management Graduates

Job Title
Employed
Median Annual Earnings
Job Title Architectural and Engineering Manager
Employed 197,000
Median Annual Earnings $150,000
Job Title Industrial Production Manager
Employed 179,000
Median Annual Earnings $109,000
Job Title Materials Engineer
Employed 25,000
Median Annual Earnings $96,000
Job Title Industrial Engineer
Employed 295,000
Median Annual Earnings $89,000

Source: Lightcast Labor Market Data, 2021. Numbers rounded to the nearest thousand.

ENGINEERING MANAGEMENT ALUMNI HAVE GONE ON TO BE EMPLOYED AT ORGANIZATIONS SUCH AS:

BMW

GOLDMAN SACHS

LOCKHEED MARTIN

EXXON

IBM

UPS

PROGRAM ADMISSION REQUIREMENTS

BACHELOR’S DEGREE

Minimum GPA of 3.0 from an accredited institution. Degree required to begin the program; completion not required at time of application.

TWO LETTERS OF RECOMMENDATION

Faculty members and/or professional colleagues.

STATEMENT OF PURPOSE

Optional, but strongly recommended.

ACADEMIC TRANSCRIPTS

Applicants must submit transcripts from all undergraduate and graduate institutions where credit was earned. You may submit unofficial transcripts during the application process. After admission, you will be required to submit official transcripts.

TOEFL/IELTS/DUOLINGO SCORES

Required for international students.

RESUME

Optional, but strongly recommended.

TUITION & COST*

$1,776

Per Credit (30 Credits)

$60

Application Fee

Fee waivers available

$250

Enrollment Deposit

Financial Aid

*Tuition based on fall 2022 rates effective September 2022. Tuition and fees are subject to change annually. Additional program fees may apply.

Key Dates & Deadlines

Term
Early Submit
Priority Submit
Final Submit
Start of Classes
Spring 2023
October 10, 2022
$250 Deposit Waiver* and Application Fee Waiver Available.
November 21, 2022
Application Fee Waiver Available and Early Application Review.
December 21, 2022
January 23, 2023

*Applicants who apply by the early submit deadline and are admitted may be eligible for a $250 deposit waiver. Applicants who receive education assistance from employers or other tuition discounts are not eligible. Other eligibility conditions may apply.

UPCOMING WEBINARS

Attendees will receive an application fee waiver.

Check back soon for more upcoming events.

FACULTY

The School of Systems and Enterprises (SSE) faculty is made up of experienced educators and active researchers who offer industry insights to Engineering Management students.

Professional headshot of Stevens faculty member, Alparslan Emrah Bayrak

Alparslan Emrah Bayrak

Assistant Professor
Professional headshot of Stevens faculty member, Chong Ee

Chong Ee

Adjunct Professor
A professional headshot of Stevens faculty member, Yeganeh Hayeri

Yeganeh Hayeri

Professor
Professional headshot of Stevens faculty member, Carlo Lipizzi

Carlo Lipizzi

Program Director and Professor
Professional headshot of Stevens faculty member, Teresa Zigh

Teresa Zigh

Teaching Associate Professor

Request Information

By providing my information and clicking the request info button, I agree to be contacted via email, phone, or text to learn more about the program selected above. Since this program is 100% online, Stevens Institute of Technology does not offer US visas to attend.