Using Analytics to Foster Business Success
Through Northeastern’s interdisciplinary Master of Science, MS, Data Analytics Engineering program, you will build on your existing engineering or science foundation to gain employment at businesses of all kinds to improve their products, processes, systems, and enterprises, all through the power of optimization, statistics, machine learning, and visualization.
The program is offered at the Boston, Massachusetts and Seattle, Washington campuses.
You’ll have the flexibility to tailor your degree to your professional goals through a number of electives across Northeastern in areas including business, engineering, healthcare, manufacturing, and urban communities, computer science, and information systems.
The masters in data analytics engineering is ideal for those who wish to develop expertise in the analysis and optimization of data to solve problems and support decision-making. For those more interested in the process of generating, collecting, and mining data by developing algorithms and computational tools, Northeastern’s Khoury College of Computer Sciences also offers a Master of Science in Data Science .
Innovative Curriculum - MS in Data Analytics Engineering
Irrespective of your engineering major, you will gain rigorous analytical skills and research experience through technically advanced core courses in operations research, statistics, data mining, database management, and visualization. You can further specialize your degree with flexible electives from diverse disciplines across colleges at Northeastern in areas such as:
- Big Data
- Smart Manufacturing
- Healthcare Analytics
- Network Science
- Machine Learning
- Advanced Optimization
- Business Analytics
- Internet of Things
Upon graduation with your MS in Data Analytics Engineering degree, you’ll be prepared to take on a data analyst position in any industry or to enter a doctoral program in areas including engineering healthcare, business, finance, security, or sustainability.
You’ll gain valuable research experience desired by employers by designing and developing analytics projects in both individual and group settings. Some recent research projects have included:
- Investigating innovative models for tumor response forecasting to personalize pre-surgical treatment for breast cancer patients
- Developing adaptive maintenance methods, standards, and metrics for monitoring and performance assurance (Mpass) of smart manufacturing equipment
- Building a robust continuous objective multimodal pain assessment sensing system (COMPASS) using physiological signals and facial expressions
The MS in Data Analytics is available on Northeastern’s campus in Boston, MA and at the regional campus in Seattle, WA.
Note: A subset of program courses are available at the regional campus.
The MS programs’ student learning outcome is the ability to use basic engineering concepts flexibly in a variety of contexts.
Over 15 graduate certificates are available to provide students the opportunity to develop a specialization in an area of their choice. Certificates can be taken in addition to or in combination with a master’s degree, or provide a pathway to a master’s degree in Northeastern’s College of Engineering. Master’s programs can also be combined with a Gordon Engineering Leadership certificate. Students should consult with their faculty advisor regarding these options.
Gordon Institute of Engineering Leadership Certificate
Students may complete a Master of Science in Data Analytics Engineering in addition to earning a Graduate Certificate in Engineering Leadership. Students must apply and be admitted to the Gordon Engineering Leadership Program in order to pursue this option. The program requires fulfillment of the 16-semester-hour curriculum required to earn the Graduate Certificate in Engineering Leadership, which includes an industry-based challenge project with multiple mentors. The integrated 32-semester-hour degree and certificate will require 16 semester hours of advisor-approved data analytics technical courses.
Engineering Business Certificate
Students may complete a Master of Science in Data Analytics Engineering in addition to earning a Graduate Certificate in Engineering Business. Students must apply and be admitted to the Galante Engineering Business Program in order to pursue this option. The program requires the applicant to have earned or be in a program to earn a Bachelor of Science in Engineering from Northeastern University. The integrated 32-semester-hour degree and certificate will require 16 semester hours of the data analytics engineering core courses and 16 semester hours from the outlined business-skill curriculum. The coursework, along with participation in co-curricular professional development elements, earn the Graduate Certificate in Engineering Business.
The Master of Science (MS) in Data Analytics Engineering is designed to help students acquire knowledge and skills to:
- Discover opportunities to improve systems, processes, and enterprises through data analytics
- Apply optimization, statistical, and machine-learning methods to solve complex problems involving large data from multiple sources
- Collect and store data from a variety of sources, including Internet of Things (IoT), an integrated network of devices and sensors, customer touch points, processes, social media, and people
- Work with technology teams to design and build large and complex SQL databases
- Use tools and methods for data mining, big-data algorithms, and data visualization to generate reports for analysis and decision making
- Create integrated views of data collected from multiple sources of an enterprise
- Understand and explain results of data analytics to decision makers
- Design and develop analytics projects
This degree program seeks to prepare students for a comprehensive list of tasks including collecting, storing, processing, and analyzing data; reporting statistics and patterns; drawing conclusions and insights; and making actionable recommendations.
The in-demand field of data analytics opens career doors around the globe and across industries, including healthcare, smart manufacturing, supply chain and logistics, national security, defense, banking, finance, marketing, and human resources.
Recent research* shows that the annual demand for data scientists, data developers, and data engineers will lead to 700,000 new recruitments by 2020. According to the U.S. Bureau of Labor Statistics, the median annual wage of professionals with these skillsets is more than $80,000.
The Academic Advisors in the Graduate Student Services office can help answer many of your questions and assist with various concerns regarding your program and student record. Use the link below to also determine which questions can be answered by your Faculty Program Advisors and OGS Advisors.
Admissions & Aid
Ready to take the next step? Review degree requirements to see courses needed to complete this degree. Then, explore ways to fund your education. Finally, review admissions information to see our deadlines and gather the materials you need to Apply.
For Shriram Karthikeyan, ME‘20, data analytics engineering, data warehousing, and analytics is nothing new—but an 8-month co-op as an ETL Developer at the Home Base Program, a nonprofit geared towards helping service members, veterans, and their families, offered an opportunity to see the outcomes driven by data warehousing. Awarded a challenge coin and a certificate […]
Data Analytics Engineering student Jignesh Jadhav, ME’20, and Computer Systems Engineering student Yiqiang Wang, ME’20, while working on co-op at Iterate Labs, developed wearable devices to help judge physical distance and alerts the wearer if someone gets to close.
Data Analytics Engineering student Aparna V. Alavilli, ME’20, was awarded the Outstanding Graduate Student Award for Experiential Learning.
Congratulations to MS in Data Analytics Engineering student Keziban Rukiye and PhD in Industrial Engineering student Weijia Jing who won 2nd place in the Doing Good with Good OR student paper competition at the annual INFORMS meeting for this paper “Enhancing the effectiveness and efficiency of food aid supply chains: an economic optimization model for USAID food for peace program’s operations in Ethiopia”