This document provides information about the Master of Science in Data Mining and Predictive Analytics program at St. John's University. The program prepares students to analyze large data sets and develop modeling solutions to support decision making. Students gain skills in statistics, predictive modeling, and data mining and specialize in either marketing analytics or healthcare analytics. There is a growing need for individuals with strong analytics skills who can derive knowledge from data and make predictions. Career opportunities for graduates exist in healthcare, retail, government, and other sectors as statisticians, analysts, and managers.

1. Master of Science:
Data Mining and
Predictive Analytics
FOR MORE INFORMATION
Please contact:
Office of Graduate Admission
Robert Medrano
Director
718-990-1601
medranor@stjohns.edu
Ronald Fechter, Ph.D.
Chair, Associate Professor
718-990-6473
fechterr@stjohns.edu
Christina Schweikert, Ph.D.
Assistant Professor
718-990-7439
schweikc@stjohns.edu
stjohns.edu/ms/datamining
M10008990NI

2. ABOUT THE PROGRAM
Predictive analytics applies statistical and data mining techniques to large data sets
in order to generate useful information, identify patterns and trends, and build models
that predict future events. Applications of these techniques are now transforming
decision making throughout business, government, healthcare, and academia.
Graduates of the M.S. in Data Mining and Predictive Analytics program gain a variety
of skills required to analyze large data sets and also develop modeling solutions to
support decision making in various domains. Students specialize in either Marketing
Analytics or Healthcare Analytics. The program prepares students to become data
mining analysts/engineers or predictive modelers.
Courses cover areas such as managerial statistics, regression and forecasting models,
database system design and data warehousing, as well as data mining and predictive
modeling.
PROGRAM BENEFITS
The M.S. in Data Mining and Predictive Analytics provides students with a distinct
competitive advantage in the current era of “Big Data.” Given the increasing quantity
of data being generated in a variety of sectors, there is a growing need for individuals
with strong analytics skills who can derive knowledge from data and make predictions
vital for executing decisions.
Analytics can be applied across disciplines and industries, such as business, finance,
healthcare, sport, hospitality, marketing, customer relationship management, and
security.
Data can be analyzed in a variety of ways and meaningful connections can be made to
provide new perspectives and insights. Different kinds of data can include electronic
healthcare records, genomic data, customer purchase history, GPS locations,
surveillance footage, Internet traffic, social network interactions, and stock prices.
Business analytics is the fastest growing category of global IT software expenditures;
approximately 69% of businesses today are interested in using analytics.
ADMISSION REQUIREMENTS
Applicants must submit the following evidence of their ability to pursue graduate
study:
• Official transcripts from all colleges/universities attended
• Personal statement (300 word essay)
• Two letters of recommendation
• IELTS/TOEFL (non-native English speakers)
• Prerequisite courses include the following undergraduate mathematics courses
or equivalent: MTH 1008 - Matrix Methods, MTH 1009 - Calculus I, MTH
1013 - Probability and Statistics I, MTH 1014 - Probability and Statistics II
PROGRAM REQUIREMENTS
To earn the M.S. in Data Mining and Predictive Analytics, students must
complete the 30 credit program within a period of no more than five years.
Students are also expected to maintain a B average (3.0 GPA) or better.
Students must choose an area of specialization selecting six credits in either
Marketing Analytics or Healthcare Analytics. Students must also complete a
Capstone project in either Applied Analytics or Software Implementation.
CAREER OPPORTUNITIES
Career opportunities for a student with an M.S. in Data Mining and
Predictive Analytics exist in many sectors including healthcare, retail, and
government. Positions can include statisticians, operations research analysts,
as well as management analysts. A variety of career choices are available
in the fields of marketing analytics, data management and analysis, and
business intelligence. The demand for professionals who are knowledgeable
in these areas is projected to grow rapidly in the coming years.