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Studying for a Data science master's degree in a US university gets you a detailed analysis and practical learning on how to apply the data science techniques in the field of your interest.

Some reasons to study in data science colleges in the USA are given below:

Top 100 Universities for Data Science in the USA

Data Science courses in the USA are highly sought-after programs. You will find many MS in data science in USA universities listed in the Top 100 QS World University Rankings 2025. Also, universities like Harvard and Stanford are offering MS data science programs ranked in the Top 10 QS Rankings.

Leading Tech Giants Hiring Data Science Graduates

The data science master's students work in top companies like Binge, Amazon, Google, T-Mobile, and Zillow in the USA. The University of the USA also offers dedicated services to its students, including an annual data science career fair. 

Explosive Job Growth in Data Science

The data science jobs rank at the top 3 in the USA according to Glassdoor and Quanthub. Also, it is overwhelming to say that the jobs after MS in data science in the USA will grow by 19% in the next two decades, more than three times the average growth of all jobs.

High Salary Potential Post-MS in Data Science

After a Master's in data science USA, the average salary ranges between 91,000 USD to 186,000 USD per annum. According to the MSDS Alumni Survey in 2019, the mean base salary of a data scientist in the USA is 124,000 USD per year. 

Top universities for Master's in Data Science in the USA include MIT, Caltech, and Cornell University. Many IVY League universities offer excellent data science programs, with a rigorous curriculum. Universities in the USA usually have 2 admission intakes - Fall and Spring, with most deadlines being between August and December. 

Here is a list of the top universities in the USA for MS in data science courses:

Now let’s delve deeper into above mentioned universities:

1. Massachusetts Institute of Technology (MIT)

MIT’s MicroMaster's in Statistics and Data Science (via MITx) offers transferable credit, emphasizing rigorous machine learning, advanced statistical modeling, and research innovation in AI-based analytics. With the world’s best curriculum and infrastructure, MIT is one of the best universities for an MS in Data Science in the US.

2. Harvard University

The data science master's program at Harvard University is jointly led by the Computer Science and Statistics faculties and administered through the Institute for Applied Computational Science. The university offers this program in 12 courses that require at least three semesters to complete. Students will also have the option to extend their studies for a fourth semester to take an additional or a master's thesis research project.

3. Stanford University

The Department of Statistics at Stanford University offers a data science graduate program. It is integrated with a statistics specialisation designed to prepare individuals for career placements after completion. This will develop strong mathematical, statistics, computational, and programming skills and provide you with fundamentals of data science education through general and focused elective requirements in the areas of interest. 

4. University of Pennsylvania

University of Pennsylvania’s Data Science master's in engineering program prepares students for a wide range of data-centric careers in technology and engineering, consulting, science, and policy-making to understand the patterns in arts, literature, or communications. The program is typically offered in one and a half to two years, blending leading-edge courses in core subjects such as big data analytics, machine learning, and statistics with a variety of elective courses.

5. University of California, Berkeley

The Master of Information and Data Science (MIDS) program at the University of California, Berkeley is an online program that working professionals can pursue at 3 different paces, according to their schedules. This one-of-a-kind program draws upon computer science, social sciences, statistics, management, and law. With experiential, project-based learning, this program aims to prepare students to be leaders in the industry.

6. Cornell University

Cornell’s MS in Data Science, offered through the SC Johnson College of Business, features project-based learning and collaborations with tech giants like IBM to drive innovative analytics research. Their MPS (Master of Professional Studies) programs have been offered for more than 20 years now. These programs offer world-class training in data science and applied statistics. This program is a great fit for anybody interested in pursuing professional careers related to business, industry, government, or scientific research.

7. University of Chicago

The University of Chicago’s data science track, developed by its Data Science Institute, features industry partnerships (e.g., Allstate) that provide hands-on projects and access to large, real-world datasets. The MSDS (Master of Science in Data Science) program is designed to help students interested in pursuing a research career in data science. This program consists of 5 core classes, 4 electives, and a comprehensive final project.

8. Yale University

Yale’s Data Science Initiative integrates coursework across its School of Management and Engineering, partnering with the Yale Center for Analytical Sciences to emphasize ethical AI and predictive modeling. The duration of the Master's program is 18-24 months. Fields of study include the main areas of statistical theory, probability theory, information theory, bioinformatics, and genetics, etc.

9. John Hopkins University

The data science master’s program at Johns Hopkins University provides training in applied mathematics, statistics, and computer science. By the end of the course, you can expect abilities required to convert data-driven problems from the actual world into mathematical ones and then solve them utilising a wide range of scientific instruments. 

10. Columbia University

Columbia University’s data science programs are jointly offered by the Graduate School of Arts and Sciences Department of Statistics and the School of Engineering and Applied Sciences. The data science students of the university have the opportunity to conduct original research, produce a capstone project, and interact with industrial partners. The program also chooses an elective track focused on entrepreneurship or a subject area covered by one of the university centres.

US universities offer admissions during Fall, Spring, and occasionally Summer. The selection of your intake period determines your university choices as well as your course selection and internship opportunities, and overall academic experience. 

Fall Intake (August to September)

The Fall intake stands as the most sought-after enrollment period, which attracts international students who want to study Data Science and other STEM fields.

• The majority of U.S. universities welcome new students during this intake period.
• The intake provides access to the widest selection of academic programs and specialized fields.
• Students can find numerous scholarship opportunities and assistantships, and financial aid programs during this intake.
• The intake period matches the typical internship schedules and campus recruitment processes.
• Students who enroll during this period will find a bigger peer network and more opportunities to build connections.

Spring Intake (January)

Students who need additional time to prepare their applications or who failed to meet Fall deadlines should consider Spring intake as their best option.

• The number of universities and courses available during the Spring intake remains lower than the Fall intake.
• The application competition remains lower during this period.
• The internship timelines do not match perfectly with the typical recruitment periods.
• Most core courses and faculty members remain accessible to students.

Summer Intake (May)

The Summer intake exists as the least popular enrollment period, which usually serves specific programs at particular universities.

• This intake option exists at only a few universities.
• The majority of programs during this period consist of short-term certificate programs together with elective courses.
• The full-time MS in Data Science programs rarely offer admission during this period.
• The availability of scholarships, together with campus placement opportunities, is restricted.

The MS in Data Science program in the USA is designed to build a strong foundation in both theory and real-world application. You’ll cover core areas like data optimisation, business intelligence, and machine learning, while also learning advanced statistical methods and software development.  The MS in Data Science syllabus provides strong, practical training to help you turn raw data into useful insights. 

It includes the following important topics:

• Data Optimisation: Improving how data is processed and stored efficiently
• Business Intelligence: Learning to find insights from large and complex datasets
• Statistical Skills: Using statistics to understand data and make decisions
• Machine Learning (ML): Teaching computers to learn from data and make predictions
• Software Development: Writing and building programs to solve data-related problems
• Data Mining: Finding patterns and useful information hidden in data

The eligibility criteria for an MS in Data Science in the USA include a compelling student profile with a good GPA (3.0/4.0), competitive test scores (GRE - 320+, GMAT - 650+), and good essays. Here are a few common eligibility criteria that you must meet:

• Bachelor's Degree: A minimum GPA score of 3.0 from your last 2 years of graded full-time study in a related bachelor’s degree, like computer science, engineering, and others.
• English Language Proficiency Test Scores: The two most popular ones accepted at every US university are IELTS and TOEFL, where you should have 7.0+ and 100+ scores, respectively.
• GRE or GMAT Scores: GMAT and GRE may not be mandatory for every university, but usually, a competitive score of 320+ in GRE and 650+ in GMAT is a good addition to your profile.
• Passport & Student Visa: Essential documents for your study abroad journey, you should have a passport and a valid student visa to study an MS in Data Science in the US.

Documents Required 

After you have thoroughly gone through the program websites and cross-checked the program-specific eligibility criteria, it is now time to arrange all the necessary documents required for starting your admission process. These documents also might vary across universities, but here is a list of general documents required by every university in the USA:

• Academic transcripts: You need all academic transcripts, starting from the board exams to your undergraduate score report.
• Letter of recommendation: You need 2-3 professional & academic references to demonstrate your ability to learn, stay consistent, and validate your contributions to projects.
• Statement of Purpose: Your statement about why you want to pursue an MS at that particular university, what your goals are, how the university can help you reach those goals, and how you can give back to society.
• Resume or CV: Most universities have a specific format for a resume, so make sure to fit/ update your CV according to that.
• Proof of your financial resources: Necessary for scholarships, you need to provide proof of funds to demonstrate your financial need.

Top QS world universities like Harvard University and Stanford University offer an MS in Data Science without a GRE. With the GRE waived, the universities can evaluate candidates holistically, considering their academic background, skills, and motivation. 

The following table contains the list of top universities offering an MS in Data Science without a GRE:

The cost of studying an MS in Data Science ranges from USD 60,000 (INR 51 Lakhs) to USD 90,000( INR 76 Lakhs). Ivy League universities are usually more expensive because of their global reputation, advanced research facilities, and strong industry networks. However, other top-ranked institutions like Caltech and public universities offer equally rigorous programs at more affordable tuition rates.

Tuition Fee

The average tuition fees for an MS in Data Science in the USA can vary from USD 60,000 to 90,000 (INR 52 to 78 lakhs), widely based on the university type. Private universities like MIT and Stanford have higher tuition fees, while public universities often offer programs with fees starting from USD 16,000 (INR 14 lakhs), making them a more budget-friendly option. Some insights on the cost of studying an MS in Data Science in the US are:

• Some of the highest-costing universities for an MS in Data Science in the US are MIT and Stanford, with tuition fees up to 80 lakhs. 
• A Master's in Data Science in the US is expensive because you get a lot of specialised resources (software, advanced computing infrastructure), labs, and training.
• Some affordable universities with low tuition fees for an MS in Data Science in the US include the University of Delaware and the University of North Texas.

Living Expense

The cost of living in the US while pursuing an MS in Data Science is typically between USD 1,200 to 2,400 per month (approximately INR 1.2 to 2.4 lakhs). The biggest chunk of your budget goes to rent, especially in metro cities, while groceries, transport, and miscellaneous expenses are areas where you can allocate your resources more mindfully to stay within budget.

Here’s an overview of how much you’ll spend living in the US while pursuing an MS in Data Science:

Some of the top scholarships for pursuing an MS in Data Science in the US are the Fulbright Scholarship and Stanford Knight-Hennessey Scholarship. From partial waivers to fully funded opportunities, these scholarships are offered by universities and global institutions and support international students across diverse backgrounds. Many of these scholarships offer up to USD 15,000 for your tuition and living expenses. 

Here’s a holistic list of scholarships for pursuing an MS in the US in Data Science:

MS in Data Science programs in the USA accept applications for fall, winter, and summer intakes, with some universities also beginning their applications in January and February. The typical admission process follows these steps:

Step 1: Choose the Right University

Start by shortlisting a list of MS in Data Science programs based on your interests, budget, and eligibility requirements. Remember to include the previously mentioned universities.

Step 2: Check Admission Requirements

Review each university’s official websites of your shortlisted universities and review the eligibility criteria and application deadlines. Then, complete the online application forms as soon as they become available. 

Step 3: Collect and Organise Documents

Gather all required documents (transcripts, test scores, resumes, etc.) and ensure you meet each program’s specific requirements.

Step 4: Submit Required Documents

Upload all necessary documents, including your academic transcripts, CV, SOP, LORs, language proficiency scores (IELTS/TOEFL), and passport copy. Ensure all documents are correctly translated and notarized if required.

Step 5: Regularly check your admission status

Regularly check your application status on the university’s portal for any updates.

Step 6: Arrange Finances & Apply for Visa

Once accepted, arrange funds to cover tuition and living expenses. Use your admission letter to apply for a student visa, ensuring all your documents are for a smooth approval. Additionally, confirm your seat at the university of your dreams.

After completing your MS in Data Science in the USA, you typically qualify for Optional Practical Training (OPT), allowing up to 12 months of work, extendable by 24 months under STEM OPT. Alternatively, employers may sponsor you for an H-1B visa or other work visas, with potential pathways to permanent residency. It's advisable to consult an immigration expert for the most up-to-date options and personalized guidance.

After your MS in Data Science, you can earn an average salary of USD 91,000 to 166,000 (INR 74.9 lakhs to 1.36 crores), making it one of the most rewarding tech careers globally. With the growing demand for data-driven decision-making, top companies like Google, Amazon, Meta, and Microsoft actively recruit data professionals. Depending on your specialization, you can pursue roles like Data Scientist, Machine Learning Engineer, or Big Data Solutions Architect. 

Here are the top job roles, recruiters, and average salary after an MS in Data Science in the US:

In addition to offering the best academics and infrastructure, US universities also organise annual data science career fairs for their students to provide individualised career support and countless opportunities to network with employers. So, if you are looking to get into the best universities in the USA for an MS in data science and have any difficulty in shortlisting the best university, connect with our 小优视频 Professionals now; they will surely guide you.