Business Analytics, M.S.

Minimum number of credits required to complete the program: 32

Minimum cumulative GPA required: 3.0

School: Girard School of Business

The M.S. in Business Analytics (MSBAI) provides a pathway for students who wish to acquire and further refine their analytics knowledge and competencies to either enter or advance their careers within the broad field of applied business analytics.

The program is designed around practical hands-on applications where data of commonly encountered business problems are introduced, with the goal of educating students on how to become proficient at transforming data into meaningful information to impact business decisions. Students will be exposed to the following tools: SAS, Python, SQL, R, Tableau, Power BI and more.

Merrimack’s MSBAI meets STEM designation requirements. International students with an F-1 visa who complete a STEM-designated degree may be eligible to apply for a 24-month STEM Extension of Optional Practical Training (OPT). This is in addition to the standard, 12-month post-completion OPT work authorization.

OPT is temporary employment directly related to an F-1 student’s area of study. While employer sponsorship for international students from U.S. universities has declined in recent years, employer demand for candidates who graduate with technical and analytical skills from reputable schools like Merrimack College remains strong.

Courses in the MSBAI are offered either 100% online or hybrid/hyflex.

Program Requirements

The M.S. in Business Analytics (MSBAI) is composed of 24 credits of core courses and 8 credits of elective courses for a total of 32 credits.

Required Courses

Complete the following required courses:

BAI 5100 - Frameworks for Business Analytics Credits: 4
BAI 5150 - Strategic Decision Making using Business Analytics Credits: 4
BAI 5200 - Data Visualization & Storytelling Credits: 4
BAI 5220 - Data Governance, Compliance & Ethics Credits: 4
BAI 5250 - Leveraging Competitive Advantage with Business Intelligence Credits: 4

Elective Course Requirements

Choose from the following electives:

ACC 5050 - Foundations of Accounting Credits: 4
ACC 5410 - Accounting Analytics Credits: 4
DSE 5001 - Introduction to Data Science and Statistics Credits: 4
DSE 5002 - SQL and Python Programming Credits: 4
Any other DSE 5000 level course or higher (which requires DSE5001 and/or DSE 5002 as a prerequisite
Any FIN 5000 level course or higher
Excluding: FIN5420 - Trends in Finance & FinTech Credits: 4
If a non-business major, MUST take FIN 5050 - Essentials of Finance Credits: 4
Any MGT 5000 level course or higher
Excluding: MGT 5120 - Supply Chain & Operations Management Credits: 2 and MGT 5360 - Leading Teams in a Dynamic Environment Credits: 4
Any MKT 5000 level course or higher
Excluding: MKT 5320 - Digital Marketing Implementation & Optimization Credits: 2

Concentrations

Students pursuing the MSBAI degree can earn a concentration by completing 12 credits in specialized areas. Common concentrations include: FinTech and Data Science, however other concentrations are available and will be discussed prior to the onboarding admissions meeting.

FinTech

This concentration focuses on the intersection of finance and innovative technology. This area of study equips students with the skills and knowledge needed to understand, develop and manage technology-driven financial services and products. Students in this concentration typically explore how emerging technologies are disrupting traditional financial institutions, reshaping customer experiences and creating new business models. The curriculum blends elements of finance, business and data analytics preparing graduates for careers in startups, investment firms, tech companies and financial institutions adapting to digital transformation.

To complete a concentration choose 12 credits from the following list of courses:

MGT 5480 - AI & CybersSecurity for Business Credits: 4
BAI 5150 - Strategic Decision Making using Business Analytics Credits: 4
FIN 5420 - Trends in Finance & FinTech Credits: 4
DSE 5001 - Introduction to Statistical Analysis Credits: 4
DSE 5002 - R & Python Programming Credits: 4

Data Science

This concentration provides students with the tools and techniques to extract meaningful insights from complex and large-scale data. It combines knowledge from statistics and domain-specific applications to solve real-world problems through data-driven decision-making. This concentration prepares students to collect, clean, analyze and interpret data across a wide range of industries. Emphasis is placed on both theoretical understanding and hands-on experience with real-world datasets and tools.

To complete a concentration choose 12 credits from the following list of courses:

DSE 5001 - Introduction to Statistical Analysis Credits: 4
DSE 5002 - R & Python Programming Credits: 4
DSE 6111 - Predictive Modeling Credits: 4
DSE 6210 - Big Data SQL no SQL Credits: 4
DSE 6220 - Big Data Hadoop & Spark Credits: 4