Analytics: Discovery Informatics & Data Sciences

Why Rutgers Master of Business and Science (MBS) in Analytics & Data Science?

  • Technical Competency: rigorous courses in Statistics & Computing 
  • Professional Competency: business Courses 
  • Career coaching & networking opportunities
  • Professionally focused
  • Practicum Project (corporate sponsored & research projects included)
  • Evening & Online classes :Part-time, Full-time, online

Overview

The Master's of Business and Science degree in Analytics prepares students for data-driven decision making. It brings together the fields of computer science, statistics, machine learning, data mining and big data. Students will obtain a variety of skills including the ability to analyze large datasets, the ability to develop modeling solutions to support decision making and a thorough understanding of how data analysis drives business decision making. The curriculum integrates science courses in analytics/data science with courses in business and management. If you are interested in a Hybrid/Online option, please visit our Analytics Hybrid/Online website.

Employment Opportunities

Opportunities in analytics are plentiful in the tri-state area (New York, New Jersey, Pennsylvania). This program prepares students for careers in predictive modeling, business intelligence, analytics, data mining in data-driven industries such as marketing, finance, health care, biotechnology and others. See this 2016 blog about the different career options in Analytics and the skills needed to succeed.

Admissions Requirements

A bachelor’s degree in any major with a GPA of at least 3.0 (a B average) and the GRE (see also the admission requirements for the MBS). Students must have at least 1 year of calculus (2 semesters and can be taken anywhere). Those without computing or statistics undergraduate may need to take introductory courses which can count towards the degree.  Unsure if you're a good fit? Attend one of our online or in-person information sessions or set up an appointment with an advisor.

Program Requirements

I.  Business Courses

A total of 19 credits are required in the business curriculum. Six courses are required - all but one of the courses are for 3 credits each. Descriptions of the required Business Courses can be found here:

Principles of Communication and Professional Development (16:137:502) (3cr)

Principles of Accounting and Finance for Science and Technology (16:137:530) (3cr)

Market Assessment and Analysis for Business and Science - Life Sciences (16:137:507) (3cr)

Ethics in Science and Technology Management (16:137:500) (1cr)

Science and Technology Management Capstone (16:137:600) (3cr)

and 2 business electives - 6 credits (e.g., project management, supply chain, Intellectual property, etc.)

II.  Science Courses

A total of 24 credits are required in the science curriculum. Five courses are required, all of which are for 3 credits each. Descriptions of the required Science Courses can be found here:

Fundamentals of Analytics (16:137:550)  (3cr)

Advanced Analytics and Practicum (16:137:551) (3cr)

Database Design and Management (17:610:557) (3cr)

Regression Analysis (16:960:563) (3cr)

Intro to Cloud Computing and Big Data (16:137:602:OC) (3cr)

and 3 science electives (9cr)

For those without computing or statistics background, the following can be taken and counted toward the degree:

Basic Statistics (01:960:484)  (3cr)

Python Methodologies for Data Science (16:137:552) (3cr)
 

ELECTIVES

Electives: Electives can be taken from a wide variety of subjects, including advanced statistics, advanced computing, business intelligence, bio-informatics, etc. See this blog about the different career types in Analytics & Data Science. Our program is flexible to meet your career objectives.

Data Science  Workshops: Students in this program are encouraged to attend the workshops in R, SAS, Stata, Python, Hadoop, etc. that run every semester. We also encourage you to attend the Practicum Poster Session. These are open to all students in the program . Please see the event list for scheduling.

Concentration Coordinators

This concentration is being coordinated in conjunction with the Rutgers Discovery Institute. While most of the course are in New Brunswick, NJ, some of the courses are also available at the Rutgers Newark and Camden campuses. For the Online-Distance Learning option, please see here.

Dr. Manish Parashar
Dr. Shantenu Jha
Dr. Deborah Silver
Dr. Debashis Kushary
Dr. William Pottenger