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Data Science, Master of Science (M.S.)

With a Master of Science degree in Data Science, you join a promising field where your skills as a data scientist will be sought after to analyze data, develop predictive models, and drive informed decision making.

A High-Demand Field With Growth Opportunities

Data science has emerged as a highly versatile and in-demand career field that spans across numerous industries. As organizations across sectors recognize the value of data-driven insights, data scientists play a pivotal role in extracting actionable information from complex datasets. The rapid advancement of technology, coupled with the exponential growth of data, ensures that data science will remain a critical field in the foreseeable future.

Our M.S. in Data Science prepares you for related careers that involve the application of computational and statistical techniques that are becoming more vital to industry and research. This is accomplished through coursework in topics such as database management systems, data mining and machine learning algorithms, data visualization, statistics, text analytics, and big data. Graduates of the Data Science program will obtain a variety of skills required to analyze large datasets and to develop modeling solutions to support decision making. 

Apply
Degree Type
MS
Area of Interest
Computing & Technology
Associated Colleges or Schools
Program Location
  • Queens Campus
Required Credit Hours
30

Program at a Glance

Specializations include Big Data Analytics, Cyber and Information Security, Healthcare Analytics, Marketing Analytics

30

Degree Credits Required

18

months (full-time)

Estimated Time To Complete

Evening Courses Available

Program Educational Objectives

The Program Educational Objectives for the M.S. degree in Data Science are that within a few years after graduation, graduates are expected to:

  1. Demonstrate an understanding of data science and computing concepts and their application in a related profession in industry or research.
  2. Continue learning and professional development to remain current in data science / computing topics.
  3. Collaborate within their profession and society in an ethical and responsible manner.

Admission Requirements

To be admitted to the M.S. program, you must have a baccalaureate degree from an accredited institution or the international equivalent before enrollment. You must also provide

  • A completed application form and nonrefundable application fee.

  • A statement of professional goals and résumé (can be uploaded as a part of the application for admission).

  • Official transcripts from all undergraduate, graduate, and professional schools attended.

  • A minimum of one recommendation, obtained from professional or academic references.

  • Official TOEFL, IELTS, or Duolingo scores are required for applicants whose native language is not English.

  • Students with international credits must also submit a course-by-course foreign credit evaluation with grade point average calculation from a National Association of Credential Evaluation Services member.

Specialize in Growing Areas of Data Science

You can choose from specialties in some of the fastest growing sectors of data science such as big data analytics, cyber information and security, healthcare analytics, and marketing analytics. As a STEM-designated program, international students are eligible for the STEM OPT extension.

Potential Careers by Specialization

Big Data Analytics

  • Big Data Engineer
  • Business Intelligence Analyst
  • Data Analyst
  • Data Architect
  • Data Mining Specialist
  • Data Scientist
  • Machine Learning Engineer

Cyber Information and Security

  • Malware Analyst
  • Security Analyst
  • Security Architect
  • Security Data Scientist
  • Security Engineer
  • Security Operations Center (SOC) Analyst
  • Threat Intelligence Analyst

Healthcare Analytics

  • Healthcare Analytics Manager
  • Healthcare Business     Intelligence Analyst
  • Healthcare Data Analyst
  • Healthcare Data Scientist
  • Healthcare Informatics Specialist
  • Healthcare Predictive Modeler

Marketing Analytics

  • Customer Insights Analyst
  • Digital Marketing Analyst
  • Marketing Analyst
  • Marketing Data Strategist
  • Marketing Operations Manager
  • Marketing Research Analyst
  • Marketing Strategy Consultant

Why St. John’s University?

Real-word, hands-on experience is the best way to prepare you for a career in data science. Pursuing a master’s degree in data science from St. John’s University provides substantial value to your career pursuits and preparation—particularly in terms of the hands-on and in-person learning opportunities it offers.

  • Gain invaluable experience to engage in practical projects
  • Collaborate with faculty members who are experts in their fields
  • Develop a proficiency in tools and techniques essential for data analysis
  • Open doors to internships, research collaborations, and future career prospects
  • AWS (Amazon Web Services) Academy Member Institution
    • Students have obtained AWS Cloud Foundation certification through the distributed big data courses.
  • Databricks University Alliance Member
Shiqi Chen ’18MS

Shiqi Chen ’18MS

“Transitioning from a medical background to the field of data science was a significant turning point in my career. The inclusive and diverse environment at St. John’s University provided me with the opportunity to pursue my passion for data science, despite coming from a nontraditional background. Since completing the M.S. program, I have witnessed significant growth in my career as a data scientist.”

Peter Tadrous ’20CCPS, ’21GCCPS

Peter Tadrous ’20CCPS, ’21GCCPS

“The Data Science program at St. John’s has been instrumental in equipping me with robust skills in statistics, data wrangling, and data visualizations. The program inspired me to see the malleability of data and how I can shape it into meaningful insights. The educators at St. John’s have fueled my curiosity and propelled a continual journey of discovery in data science.”

St. John's University Crest on top of gate

Brad Rose ’20MS

“I was thankfully able to use my military benefits to continue my higher education at St. John’s, which led to employment in the fintech industry at J.P.Morgan. I did so late in life; it’s never too late to get an education. For those of you who are getting one early, remember how fortunate you are to have the support structure and ability to do so.”

Degree Requirements

The M.S. program in Data Science requires 30 credits that include the following:

Core Courses (9 credits required)

  • CUS 510 Database Management Systems
  • CUS 610 Data Mining and Predictive Modeling I
  • CUS 615 Data Mining and Predictive Modeling II

Data Analysis/Applied Statics Courses (6 credits chosen from the following)

  • BUA 602  Business Analytics
  • BUA 609 Advanced Managerial Statistics
  • BUA 633 Predictive Analytics and Forecasting Models

Elective Courses (6 credits in one of the following areas)

  • CUS 620 Introduction to Programming for Analytics
  • CUS 625 Data Visualization Programming
  • CUS 635 Web Data Mining
  • CUS 640 Natural Language and Text Processing
  • CUS 675 Database Programming
  • CUS 680 Distributed Big Data Analytics I
  • CUS 681 Distributed Big Data Analytics II

Capstone Course

  • CUS 690 Applied Analytics Project

Specialization (6 credits in one of the following areas):

  • Big Data
    • CUS 680 Distributed Big Data Analytics I
    • CUS 681 Distributed Big Data Analytics II
  • Cyber and Information Security
    • CYB 611 Foundations in Cyber Security
    • CYB 615 Protection of Digital Infrastructure
    • CYB 621 Cybersecurity Laws, Regulations, and Best Practices
    • CYB 625 Principles of Secure Scripting and Cryptography
    • CYB 711 Intrusion Detection and Analysis
    • DFR 711 Cyber-Forensic and Malware Analysis
  • Healthcare Analytics
    • HCI 520 Medical and Health Informatics
    • HCI 525 Applied Healthcare Analytics
  • Marketing Analytics
    • MKT 600 Decisions in Marketing Management
    • MKT 611 Data-Driven Marketing
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The Institute for Data Science

 

The Institute for Data Science at St. John’s University serves as a hub for research activities, with an emphasis on data mining and analytics. Researchers explore opportunities for data science initiatives among disciplines within The Lesley H. and William L. Collins College of Professional Studies and across the University.

Meet Our Faculty

Profile photo for Fazel Keshtkar
  • Associate Professor

Department

Computer Science, Mathematics and Science

Contact Us

We are here to answer any questions you may have about the M.S. in Data Science degree program and the admission process.

Dr. Christina Schweikert

Associate Professor

St. Augustine Hall Queens 2-082

Office of Graduate Admission
718-990-1601
[email protected]

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