Analytics: Discovery Informatics & Data Sciences (Online)

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

 

Overview

This concentration is a fully Online version of the traditional Master of Business & Science (MBS) degree with a concentration in Analytics. Classes will be online courses. Students are expected to complete the program in about 2 years. There is a 1-week on-campus meeting every year. See below for more information and application instructions.

If you are interested in our in-person/hybrid analytics option, click here​​.

Analytics Pathways

To assist students coming in with experiences in science or business areas, we have created pathways within the Analytics concentration to build on the student’s existing skills. All Analytics students must take the core business and science (analytics) courses, but within each pathway, students have required electives to assist in their professionally guided curriculum.

For students with a background in Engineering, Analytics, Computer Science, Mathematics, Statistics, and related areas, the student is guided towards our traditional Technical Analytics track where your advisor will work with you to come up with your professionally guided curriculum based on your experience, professional background, and career goals.

For students with a background in health/healthcare related areas (undergrad degree in Biology, Pharmacy, Psychology, Pharmaceutical Sciences, and related areas), students are guided to our Health Informatics pathway.

For students with Finance related areas (undergrad degree in Finance, Business, Economics,

, Business Intelligence, or related areas), students are guided to our Finance Analytics pathway.​
 

Business Core Courses - 5 courses (13 credits):
 Principles of Finance and Accounting (16:137:530); Market Assessment & Analysis (16:137:507); Principles of Communication  & Professional Development (16:137:502); Science & Technology Management Capstone (16:137:600); Ethics (16:137:500)
Analytics Core Courses - 5 courses (15 credits):
Fundamentals of Analytics (16:137:550); Database and Data Warehousing (16:137:603 OR 17:610:557); Intro to Cloud Computing & Big Data (16:137:539); Regression Analysis (16:137:602); Advanced Analytics & Practicum (16:137:551)
Health Informatics Pathway

Admissions Requirements: A Degree and/or work experience in healthcare, pharmaceutical sciences, psychology, and related areas. A year of calculus is required (Calc 1 and Calc 2). For those that did not take Calc 2, statistics can be substituted:  Calc 1 and  Stats 1 and 2 OR Calc 1 and  BioStats 1 and 2 OR Calc 1 and Stats and Regression (separate) courses.

Required Business Electives
(2 courses = 6 credits)

- Bus. Intelligence Visual Analytics (16:137:553)
- Project Management (22:799:691)

Required Analytics Electives
(3 courses = 9 credits)

- Python Methodologies (16:137:552)
- Interpretation of Data (16:960:586)
- 1 Elective (See sample list HERE)

Finance Analytics Pathway

Admissions Requirements: For those with a business, finance, economics, business intelligence, or accounting degree. A year of calculus is required (Calc 1 and Calc 2). For those that did not take Calc 2, statistics can be substituted. Calc 1 and  Stats 1 and 2 OR Calc 1 and economic modeling and Econometrics.

Required Business Electives
(2 courses = 6 credits)

- Bus. Intelligence Visual Analytics (16:137:553)
- Risk Management (22:390:670 or equivalent)

Required Analytics Electives
(3 courses = 9 credits)

- Python Methodologies (16:137:552)
- Data Str. & Algorithms/ Problem Solving in Python (56:137:501)
- 1 Elective (See sample list HERE)

Technical Analytics Pathway

Admissions Requirements: For those interested in analytics, typically with an engineering, stats, statistics, mathematics,operations research, or related degree. Must have taken Calc 1 & 2.

Required Business Electives
(2 courses = 6 credits)

- Bus. Intelligence Visual Analytics (16:137:553)
- 1 Elective (See sample list HERE)

Required Analytics Electives
(3 courses = 9 credits)

- Applied AI (16:137:602)
- 2 Electives (See sample list HERE)

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 2018 blog about the different options in Analytics and the skills needed to succeed. Understand how the skills differ by industry, and see below for detailed skills by industries relating to some of our Analytics Pathways. Our students have excellent outcomes, with a 96% employment rate within 6 months of graduation, working for companies such as JP Morgan, Barclays Investment Bank, Bloomberg LP, the Janssen Pharmaceutical Companies of Johnson & Johnson, Saatchi & Saatchi Wellness, Deloitte, Accenture, and more.

Matching Skills to the Careers You Want: We frequently perform labor analysis of skills requested by employers by industry. The four industries we target in a broad labor analysis match to our Analytics Pathways. These account for about 40% of the analytics roles requested by employers in 2018 (see chart below). These skills are utilized to help match students to electives and core courses. See HERE for further discussion on how we help match the skills you want to our courses.

 

Admissions Requirements

Technical Analytics: A bachelor’s degree in Engineering, Engineering Management, Statistics, Mathematics, Computer Science, Industrial Engineering, Operations Research, or related degree, 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). Students must also have an undergraduate level programming course and statistics course for this track. Those without an undergraduate level course in both programming and statistics may need to take introductory course(s) 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.

Finance Analytics: A bachelor’s degree in Finance, Accounting, Business, Business Management, Economics, Financial Economics, Business Intelligence, or related degrees 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). For the Finance Analytics track, if you do not have Calc 2, it may be substituted for: 2 semesters of financial modeling or 2 semesters of economics modeling (econometrics and a second upper level economics course) or business statistics level 1 and 2. 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.

Health Informatics: A bachelor’s degree in Biology, PreMed, Psychology, Pharmaceutical Sciences, or related degrees 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). For the Health Informatics track, if you do not have Calc 2, it may be substituted for: Biostatistics level 1 and 2 (2 semesters/1 year), or an upper level statistics and regression course (2 semesters/1 year). 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.

The On-Site Residency in mandatory for all online students, including out-of-state students. Click here for more information.

 

Electives

Electives: Electives can be taken from a wide variety of subjects, including advanced statistics, advanced computing, business intelligence, bio-informatics, etc. Our program is flexible to meet your career objectives. Examples of Business, Health Informatics, Technical Analytics, and Financial Analytics Electives.

Externship Exchange: Students in this program are able to participate in company, nonprofit, research, and/or government real world projects to gain experience. These projects are done on campus in any semester (can be done every semester – fall, spring, summer), and are run by our Externship Exchange Coordinator, Dr. Christie Nelson (cnelson@dimacs.rutgers.edu). Projects can be done for volunteer/student club, or as an elective course to count toward the degree. These projects can be done remotely and in evenings for students working full time, online/hybrid students can participate, and full time/part time students can participate in daytime or evening to accommodate their schedules. These projects are yet another way to gain experience and help students to get to their professional goals.

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.

 

Professional Services, Opportunities & Outcomes

To read more about our professional services (resume review, career services, and workshops), our Externship Exchange program (company/nonprofit projects that can be done in evenings in addition to working full time, remotely, or for full/part time students as elective credit or for “club”/volunteer), and more, see our Corporate Connections page. Our students have excellent outcomes, with a 96% employment rate within 6 months of graduation, working for companies such as JP Morgan, Barclays Investment Bank, Bloomberg LP, the Janssen Pharmaceutical Companies of Johnson & Johnson, Saatchi & Saatchi Wellness, Deloitte, Accenture, and more. We have a full time career services specialist for the MBS department, an executive coach, and real world on campus project opportunities to help get you to your professional goals.

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.

Questions please contact: Dr. Christie Nelson cnelson@dimacs.rutgers.edu

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

Dr. Christie Nelson 
cnelson@dimacs.rutgers.edu

-- 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.