Ph.D. in Business Data Science

Degree Requirements

Students must maintain a cumulative GPA of 3.0 or better. Students are expected to conduct innovative and independent research and have their research findings published in peer-reviewed scholarly journals and academic conference proceedings. By the beginning of the first semester, upon the approval of the PhD program academic advisor, student must have filed a plan of study that lists the courses to be taken and the timeline of study. Any modification to the plan of study must be approved by the PhD program academic advisor and dissertation advisor (if chosen).

Course Requirements

By the end of year one, student must have completed any assigned bridge courses upon the PhD program academic advisor’s suggestion with a grade of at least a B in each course. 

A student entering the program with only a Bachelor’s degree in related areas shall take 36 credits of advanced courses beyond the Bachelor’s degree with the approval of the PhD program academic advisor. The 36 credits shall include six core courses and six elective courses, and are in addition to the credits for dissertation research. Among the 36 credits, at least 12 credits must be of the 700 level courses or courses with PhD track projects. 

A student entering the program with a Master’s degree or above in the related areas shall take 18 credits of advanced courses beyond the Master’s degree or its equivalent with the approval of the PhD program academic advisor.  These 18 credits are in addition to the credits for dissertation research. Among the 18 credits, at least 12 credits must be of the 700 level courses or courses with PhD track projects. 

All core courses are listed in Table DR-1. Table DR-2 provides a partial list of the elective courses available to program students. In addition to the listed elective courses, a student may take other special topic courses, at most two of which can be counted as electives, subject to the approval of the PhD program academic advisor.

Table DR-1: List of Core Courses
MGMT 682Business Research Methods I3
MGMT 683Business Research Methods II3
MGMT 635Data Mining and Analysis3
or CS 634 Data Mining
CS 631Data Management System Design3
or IS 631 Enterprise Database Management
MATH 660Introduction to statistical Computing with SAS and R3
MATH 644Regression Analysis Methods3
Table DR-2: List of Elective Courses
ACCT 615Management Accounting3
CS 610Data Structures and Algorithms3
CS 632Advanced Database System Design3
CS 675Machine Learning3
or CS 732 Advanced Machine Learning
CS 750High Performance Computing3
CS 645Security and Privacy in Computer Systems3
or CS 708 Advanced Data Security and Privacy
CS 666Simulation for Finance3
ECE 601Linear Systems3
ECE 673Random Signal Analysis I3
ECON 610Managerial Economics3
EM 655Management Aspects of Information Systems3
FIN 600Corporate Finance I3
FIN 610Global Macro Economics3
FIN 624Corporate Finance II3
FIN 626Financial Investment Institutions3
FIN 627International Finance3
FIN 634Mergers, Acquisitions, and Restructuring3
FIN 641Derivatives Markets3
FIN 650Investment Analysis and Portfolio Theory3
FIN 655Financial Innovations and Market Failures3
HRM 601Organizational Behavior3
HRM 630Managing Technological and Organizational Change3
IE 650Advanced Topics in Operations Research3
IE 687Healthcare Enterprise Systems3
IE 688Healthcare Sys Perfor Modeling3
IS 634Information Retrieval3
IS 665Data Analytics for Info System3
IS 665Data Analytics for Info System3
IS 682Forensic Auditing for Computing Security3
IS 684Business Process Innovation3
IS 687Transaction Mining and Fraud Detection3
IS 688Web Mining3
MATH 699Design and Analysis of Experiments3
MGMT 620Management of Technology3
MGMT 630Decision Analysis3
MGMT 640New Venture Management3
MGMT 641Global Project Management3
MGMT 649Convention, Creativity and Innovation3
MGMT 656Public Policy and Business3
MGMT 670International Business3
MGMT 680Entrepreneurial Strategy3
MGMT 688Information Technology, Business and the Law3
MGMT 691Legal and Ethical Issues3
MGMT 692Strategic Management3
MGMT 710Forecasting Methods for Business Decisions3
MIS 625Management Strategies for E-Commerce3
MIS 645Information Systems Principles3
MIS 648Decision Support Systems for Managers3
MIS 680Management Science3
MRKT 620Competing in Global Markets3
MRKT 631Marketing Research3
MRKT 636Design and Development of High Technology Products3
MRKT 637Marketing Communications and Promotions3
PTC 628Analyzing Social Networks3

Full-time PhD students are required to register each semester for a zero-credit course: SOM 791 Graduate Seminar, and to attend at least 50% of all School-wide seminars each semester. 

The requirement of pre-doctoral research (SOM 792) and doctoral dissertation (SOM 790) credits are described at: http://www5.njit.edu/graduatestudies/content/new-phd-credit-requirements/

Qualifying Examination

All PhD students are required to take a qualifying examination by the end of year one, and must pass the qualifying examination by the end of year two. The qualifying examination covers subject matter drawn from the core courses.

Dissertation Advisor and Dissertation Committee

Students are recommended to choose a dissertation advisor as soon as possible, but no later than 3 months after passing the qualifying exam. By the end of year three: student must have a dissertation committee established and the dissertation proposal must be successfully defended.

Dissertation Defense

Full-time PhD students must defend the dissertation successfully by the end of the sixth year in the PhD program.

Please refer to the following website for other Institution-wide policies and procedures for Ph.D. programs: http://www5.njit.edu/graduatestudies/sites/graduatestudies/files/policies-procedures-doctoral_updated_2015.pdf