Masters in Data Science in USA

Top Universities, Eligibility, Scholarships & More

  1. USA
  2. Masters in Data Science in USA
7 min

Data Science is a rapidly growing field, and pursuing a Master of Science (MS) in Data Science in the USA can lead to a rewarding career, given the country's reputation for quality education and its leading role in technology and innovation. Before applying to top universities in USA for MS in data science it's crucial to thoroughly research programs consider your career goals, and evaluate factors such as curriculum, faculty expertise, location and financial considerations to find the best fit for your academic and professional aspirations.

Master of Science in Data Science

MSc in Data Science

fall Intake
2 years
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Pace University

Westchester, USA

Master of Science in Data Science

fall, spring, summer Intake
1.5 years
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MS in Data Science

fall, spring Intake
2 years
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MSc in Data Science

fall, spring Intake
2 years
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M.S. in Data Science

fall, spring Intake
2 years
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MSc in Data Science

fall, spring Intake
2 years
Tuition Fee
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Eligibility Requirements

When considering the eligibility for data science in USA, especially for a Master's in Data Science, it's important to check the requirements carefully. Universities typically look for a bachelor's degree in a field like computer science or engineering. They may also expect you to have completed certain foundational courses, including programming, statistics, and math. Additionally, standardized tests such as the GRE are often part of the application process.

For non-native English speakers, demonstrating English proficiency through TOEFL or IELTS scores is usually necessary.

Academic Qualifications:

Academic qualifications required for

Bachelor's Degree

Need a bachelor's degree in data science, mathematics, statistics or a related field

GPAMost universities require a GPA of at least 3.0 on a 4.0 scale, which is like getting scoring around 80% overall

Standardized Test Scores:

GREGRE scores with a minimum of 130 in verbal, 140 in quantitative, and 2.5 in writing analysis. (Overall 280 - 320)
Language Proficiency TestsInternational applicants generally need to prove their English skills by taking standardized tests. They usually have to achieve certain minimum scores.
  • IELTS: 6.0 - 7.0
  • TOEFL: 80 - 90

Additional Requirements:

  • Official Transcripts: Your academic records show your grades from previous studies.
  • Statement of Purpose (SoP): A personal essay explaining your goals and reasons for pursuing the program.
  • Letters of Recommendation (LORs): Statements from professionals in your field or related areas endorsing your capabilities and potential for success.
  • Work Experience: US MS programs in fields like health, education, and tech often require work experience. It helps applicants, even those with lower grades, prepare for their careers.

Application Process and Requirements

Once you understand what you need to qualify, it's time to learn how to apply for the top colleges in USA for Ms in data science

Admission Process for Getting into top universities in USA for MS in data science: 

  • Research and Selection: Identify the desired course and research the Top colleges for MS in data science in USA. Explore university websites for requirements, eligibility, admission procedures, and fees.
  • Application Submission: Initiate the online application process and provide all necessary details. Upload required documents such as transcripts, essays, test scores, LOR, and SOP.
  • Document Upload and Fee Payment: Ensure accurate document uploads and apply. Pay the application fee according to the university's guidelines.
  • Review and Waiting Period: Await communication from the university regarding your application status. Be patient during the review process.
  • Admission Decision: Follow instructions upon selection. Apply for the I-20 visa for F-1 student status.

Data Science Curriculum and Skills Required

When exploring top universities in USA for MS in data science, understanding the curriculum and required skills is essential. These programs offer a comprehensive blend of theoretical knowledge and practical skills needed to excel in the dynamic field of data science.

Core Courses

Core courses in a Master's in Data Science program typically cover foundational subjects that provide essential knowledge and skills for the field.

Here are some core courses offered by the top colleges in USA for MS in data science:

Statistics for Data ScienceLearn how to make sense of data through numbers. It's all about using statistics to find patterns and answer questions.
Machine LearningThis is where you teach computers to learn on their own from data. It's like training a robot to make smart decisions.
Data MiningDive into large sets of data to find the hidden treasures. It's like being a detective but for Dat
Data VisualizationLearn to turn data into visual stories that people can understand. It's about making complex info look simple and clear
Database ManagementGet the skills to organize and manage data in databases. It's like setting up a super-organized digital filing system.


Elective Courses

Elective courses, on the other hand, offer students the flexibility to choose specialized topics based on their interests and career goals.

Here are some elective courses that the best colleges for MS in Data Science in  USA offer:

Big Data Analytics

Learn how to deal with really, really big sets of data and get insights from them. It's like data science but for giant datasets
Deep LearningDive deeper into machine learning with complex models. Think of it as teaching a computer to think and learn like a human brain.
Business IntelligenceUse data to make smart business decisions. It's about using data to figure out how to make a company more successful.
Data Ethics and PrivacyLearn about the right and wrong ways to use data, especially how to keep people's information safe and private.
Natural Language ProcessingTeach computers to understand human language. It's like helping a robot read and understand books or conversations.

Soft Skills Development

The Master of Science (MS) in Data Science programs in the USA, while primarily focused on developing technical competencies in areas such as machine learning, statistical analysis, and big data technologies, also places a significant emphasis on the development of soft skills.

Here are some key soft skills that MS in Data Science programs in the USA aim to develop:

  • Communication Skills: Essential for explaining complex data to non-technical stakeholders.
  • Critical Thinking and Problem-Solving: For creatively addressing and solving data-related problems.
  • Collaboration and Teamwork: Vital for working effectively with cross-functional teams.
  • Ethical Judgment and Integrity: Important for navigating data privacy and ethical considerations.
  • Adaptability and Continuous Learning: Necessary to keep up with the rapidly evolving field.
  • Project Management: For efficiently leading data projects from start to finish.
  • Leadership: Critical for those aiming for management positions.

These skills are developed through a mix of project-based learning, group work, and internships, preparing graduates for successful careers in data science.

Financial Aid and Scholarships

To ease the financial burden of pursuing a Master's in Data Science in the USA, top universities offer a variety of scholarships and financial aid options. These opportunities are vital for students considering the cost of such programs. With funding sources ranging from government scholarships to private foundations and university fellowships, students have multiple avenues to manage the expenses associated with their education. 

This approach not only recognizes academic excellence but also provides practical support through loans and work-study programs also knows the cost of MS in data science in USA.

University Scholarships

Many universities offer scholarships specifically for data science students. These can be merit-based, need-based, or both. They may cover a portion of the tuition fees or provide a stipend for living expenses. It's essential to check the data science department's website of the universities you're interested in for scholarship opportunities.

Research Assistantships

Research assistantships are a great way to get involved in academic research while receiving financial support. As a research assistant, you'd work on specific research projects under the guidance of a faculty member. In return, you might receive a tuition waiver and a stipend.


Fellowships are prestigious awards that can provide significant financial support. They are often merit-based and may cover tuition and living expenses. Fellowships can be offered by universities, private foundations, and government agencies.

External Scholarships

Numerous organizations and foundations offer scholarships to students pursuing degrees in STEM fields, including data science. Examples include the National Science Foundation (NSF) and various professional organizations related to data science and technology.

On-Campus Employment

Most top universities in the USA for MS in data science allow students to work part-time on campus. Jobs can range from library assistants to lab technicians, providing a steady income to help with living expenses.


While not a form of aid, federal and private loans can help cover the cost of your education. Federal loans usually offer lower interest rates and more flexible repayment options than private loans.

Career Opportunities

Going for a top colleges in USA for MS in data science opens up many job opportunities after MS in DS in USA. These schools give a top-notch education and lead to well-paying and satisfying jobs in the fast-growing data science area.

This high demand translates into attractive salary after masters Data Science in the USA, making it not just a fulfilling career path but also a financially rewarding one.

In essence, pursuing a Master's in Data Science at a leading US institution is a wise investment for those passionate about data, aiming for high salary potential and job satisfaction in a dynamic field.

Here are some career options you can explore: 

Job Roles Average Salary 
Machine Learning Engineer $1,65,072 per year 
Data Scientist $1,54,755 per year 
Big Data Developer$1,67,097 per year
Database Administrator$100,891.35 Per year
Analytics Engineer$118,766 per year

Machine Learning Engineer

They teach computers to learn and make decisions from data without being directly programmed. Think of it like training a robot to make smart choices.

  • Inc.
  • Intel Corporation
  • Cognizant
  • General Electric        

Data Scientist

A data scientist digs into big piles of data to find useful insights. It's a bit like being a detective, but for data, helping companies make smart decisions.

  • IBM
  • Apple
  • Google
  • Microsoft

Big Data Developer

Big data developers handle huge amounts of data and make sure it's organized and usable. They're like the architects of data, building the systems that can handle big data sets.

  • Northrop Grumman Corporation
  • Google
  • Intel Corporation         
  • Inc.

Database Administrator

They take care of databases where companies store their information. They're like librarians for data, making sure everything is safe, organized, and easy to find.

  • General Electric
  • Lockheed Martin Corporation
  • Cognizant
  • Apple

Analytics Engineer

An analytics engineer uses data to help companies figure out how to improve their products or services. They set up the tools and methods to turn data into helpful advice, kind of like setting up a science experiment to understand what's happening.

  • Google
  • IBM
  • Inc.
  • Intel Corporation 



Pursuing a master's from top universities in USA for MS in Data Science opens doors to exciting career opportunities and equips students with the necessary skills to thrive in the ever-evolving field of data science. With a rigorous curriculum, cutting-edge research opportunities, and a supportive academic environment, these institutions lay the foundation for success in the data-driven world of tomorrow.

Frequently Asked Questions (FAQs)

Can i do major in datascience with mechanical degree with 7.26cgpa?

A person with a mechanical degree and a 7.26 CGPA (Grade Point Average) may be able to pursue a graduate degree in data science, but it would depend on the specific requirements and admissions policies of the universities or institutions in question. 

Many graduate programs in data science require a strong academic background in math, statistics, and computer science, which may be more closely aligned with a traditional computer science or electrical engineering degree. Additionally, a certain level of experience and skill in programming and data analysis is also often required.

There are many universities and institutions around the world that offer graduate programs in data science, including universities in the following countries:

  1. United States: MIT, Stanford University, University of California, Berkeley, Harvard University, Carnegie Mellon University, among others.
  2. United Kingdom: University of Cambridge, Imperial College London, University of Oxford, among others.
  3. Germany: the Technical University of Munich, Ludwig Maximilian University of Munich, among others
  4. France: Sorbonne University, École Normale Supérieure Paris-Saclay, among others
  5. Australia: Monash University, University of Melbourne, and University of Sydney, among others

These are just a few examples of the many universities around the world that offer graduate programs in data science, and there are many other options available depending on your location and interests. Keep in mind that this is not a comprehensive list and the availability of the program and specific requirements may vary in different Universities.

If you have any other questions feel free to leave a comment below.

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