About Master’s in Data Analytics
A Master’s in Data Analytics is a specialized degree that is only offered by a handful of universities around the world. However, graduating with an MS in Data Analytics would give you a significant competitive edge in many industries as demand for the skills of data analysis is growing at a breakneck pace. The Bureau of Labor Statistics of the USA suggests that the growth in jobs for data analysts is much faster than the growth for other job roles.
Additionally, many people choose to do a dual degree when they sign up for their Master’s in Data Analytics. A few examples of these dual degrees are given below.
- MS in Data Analytics and Information Management
- MS in Data Analytics and Operations Research
- MS in Data Analytics and Risk Management
Programming is at the core of data analytics in the modern context, as are data forecasting and statistical modeling for big data. Graduates of the program will find ample job opportunities in industries such as technology, finance, consulting, and retail.
For fresh graduates, the average salary after an MS in Data Analytics is between $86,000 to $90,000 per annum. After a couple of years of experience, that could easily increase to $100,000+.
For now, let’s kick things off by looking at the best countries to study for a Master’s in Data Analytics.
Top countries to study an MS in Data Analytics
The country you choose for your Master’s in Data Analytics will have a big impact on your overall experience and career. Below are some of the best countries for a Master’s in Data Analytics.
The United States
The USA is the most popular choice for students looking to pursue a Master’s in Data Analytics. 19 out of the top 72 Data Analytics programs in the world are in the United States, as per the 2024 QS University Rankings. The USA is home to a lot of the world’s most prestigious universities, from the likes of MIT and Stanford to Harvard and Duke. Most MS in Data Analytics programs in the USA include either a ‘capstone project’, thesis, or internship as part of the course. The average salary after an MS in Data Analytics is $86,000, according to Glassdoor.com.
China (Including Hong Kong)
In second place we have the PRC, and the province of Hong Kong. Mainland China has 5 of the top 72 universities for an MS in Data Analytics. Following close on its heels is Hong Kong, which is home to 4 more of the top 72 universities for data analytics. Out of those 9 schools, the Hong Kong University of Science and Technology is ranked the highest, at #10. Other names on the list include the University of Hong Kong, Tongji University, and Wuhan University. Studying in China will truly be an experience like no other, especially with the country opening up so much in the past few years.
- Australia
In the number three position is the land down under, with 7 out of the top 72 universities for an MS in Data Analytics. The big names on this list include the likes of UNSW, the University of Melbourne, Monash University, and UTS Sydney. Of these, UMelbourne is ranked the highest among the Australian MS in Data Analytics programs, at #26 globally. If you are looking to pursue an MS in Data Analytics abroad, consider Australia, as the country is a popular choice for international students.
- The United Kingdom
6 out of the top 72 universities for an MS in Data Analytics are in the UK. Universities like Oxford, Imperial, Edinburgh, and UCL feature on the QS Ranking list, alongside King’s College and Lancaster University. A Master’s in Data Analytics can lead to rewarding careers in the UK. According to Glassdoor, graduates can expect an average starting salary of £32,000, which can increase to £40,000 within a few years of experience.
Top universities in the world for an MS in Data Analytics
In this section, we’ll take a look at the best universities in the world for a Master’s in Data Analytics. Here are the top 25, according to the QS World University rankings for 2024.
| Rank | University Name | University Location | School Name |
| 1 | Massachusetts Institute of Technology (MIT) | Cambridge, United States | Sloan School of Management |
| 2 | Carnegie Mellon University | Pittsburgh, United States | Tepper School of Business |
| 3 | University of California, Berkeley (UCB) | Berkeley, United States | Haas School of Business |
| 4 | University of Oxford | Oxford, United Kingdom | Saïd Business School |
| 5 | Harvard University | Cambridge, United States | Harvard Business School |
| 6 | National University of Singapore (NUS) | Singapore, Singapore | NUS Business School |
| 7 | ETH Zurich – Swiss Federal Institute | Zurich, Switzerland | Department of Management, Technology, and Economics |
| 8 | Nanyang Technological University, Singapore (NTU) | Singapore, Singapore | Nanyang Business School |
| 9 | University of Toronto | Toronto, Canada | Rotman School of Management |
| 10 | The Hong Kong University of Science and Technology | Hong Kong, Hong Kong SAR | HKUST Business School |
| 11 | EPFL | Lausanne, Switzerland | College of Management of Technology |
| 12 | University of Washington | Seattle, United States | Foster School of Business |
| 13 | Georgia Institute of Technology | Atlanta, United States | Scheller College of Business |
| 14 | University of Illinois at Urbana-Champaign | Urbana-Champaign, United States | Gies College of Business |
| 15 | Princeton University | Princeton, United States | Princeton School of Public and International Affairs |
| 16 | Cornell University | Ithaca, United States | SC Johnson College of Business |
| 17 | New York University (NYU) | New York City, United States | Stern School of Business |
| 18 | UCL (University College London) | London, United Kingdom | School of Management |
| 19 | Imperial College London | London, United Kingdom | Imperial College Business School |
| 20 | University of Pennsylvania | Philadelphia, United States | Wharton School |
| 21 | California Institute of Technology (Caltech) | Pasadena, United States | Not applicable (focused on science and engineering) |
| 21 | The University of Edinburgh | Edinburgh, United Kingdom | University of Edinburgh Business School |
| 23 | Politecnico di Milano | Milan, Italy | School of Management |
| 24 | Seoul National University | Seoul, South Korea | College of Business Administration |
| 25 | The University of Hong Kong | Hong Kong, Hong Kong SAR | Faculty of Business and Economics |
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In the next section, we’ll give you an overview of the course content that is covered in an MS in Data Analytics.
Course curriculum for an MS in Data Analytics
Each university tailors their course content to a great extent. However, during our in-depth research, certain “modules” or topics were common to 90% of the programs we analyzed. Here is the syllabus for an MS in Data Analytics.
| Curriculum Components | Skills Acquired | Typical Courses |
| Statistical and Quantitative Analysis | Analyzing and interpreting complex data sets | Statistical Analysis, Quantitative Methods, Foundations of Data Analytics |
| Programming and Data Science Tools | Proficiency in programming languages like Python and R | Python Programming for Data Science, Data Science Tools |
| Machine Learning and Advanced Analytics | Predictive modeling and algorithmic data analysis | Machine Learning, Advanced Analytics, Data Driven Knowledge Discovery |
| Data Management and Big Data Technologies | Managing large datasets and databases | Data Management, Big Data Technologies, Enterprise Infrastructure for Data Analytics |
| Business and Data Strategy | Applying data insights to business decision-making | Business Analytics, Data Analytics for Emerging Technologies, Applied Analytics—Case Studies |
| Visualization and Communication | Presenting data insights effectively | Visual Analytics, Communication & Persuasive Data Presentation, Data Visualization & Cloud Technologies |
| Ethics and Data Governance | Ethical data handling and compliance | Business Ethics & Data Governance |
| Capstone Project or Internship | Applying skills in real-world scenarios | Capstone Project, Internship |
Now that we’ve covered the curriculum, let’s talk about the eligibility for an MS in Data Analytics.
Eligibility for studying an MS in Data Analytics
Universities have different requirements for an MS in Data Analytics. The following overview will help you get a sense of the different criteria you might be expected to fulfill.
- Bachelor’s Degree
You’ll need an undergraduate degree from an accredited university. A background in fields with strong quantitative elements, such as economics, engineering, or computer science, is often seen as advantageous.
- Prerequisite Courses
Expect to show competence through coursework in areas such as Linear Algebra, Statistics, Multivariable Calculus, and Probability. These foundational courses are crucial for handling the advanced analytical content of the MSBA program.
- Programming Skills
Proficiency in programming languages like Python, R, SQL, or Java is essential. Some programs may also value familiarity with other languages like C++, especially for data-intensive analytics tasks.
- Standardized Tests
While GRE or GMAT scores are commonly required, some programs might offer waivers, particularly if you have a strong quantitative background or substantial professional experience.
- English Language Proficiency
Non-native English speakers usually need to demonstrate proficiency through TOEFL or IELTS scores. A waiver might apply if you completed a four-year undergrad degree in English.
- Letters of Recommendation (LOR)
You will need at least one LOR for an MS in Data Analytics. Most programs ask for one (minimum), though two are typically preferred. These can be either from your professional work environment or academic mentors if more relevant.
- Statement of Purpose (SOP)
Similar to a Letter of Recommendation (LOR), a Statement of Purpose (SOP) is a crucial component of your MS in Data Analytics application. An SOP not only outlines your academic and professional background but also highlights your future goals and aspirations, providing detailed reasons why you would be an excellent fit for the program.
While not always mandatory, related work or research experience in a quantitative discipline can significantly strengthen your application. This is similar to how hands-on experience with supercars can be invaluable in a sales or technical role at a luxury car dealership. Enabling you to have real-world insights that academic training alone cannot offer.
Next, let’s find out more about GMAT and GRE requirements for an MS in Data Analytics.
GMAT/GRE requirements for studying an MS in data analytics
GMAT or GRE scores are not typically required for admission into an MS in Data Analytics program. Many universities, like the University of Melbourne in Australia, explicitly state that these scores are not necessary.
However, it’s important to confirm the specific requirements of each university you’re interested in, as some may still request or recommend these scores. If you have a strong quantitative background, such as high grades in undergraduate courses like linear algebra, you may be able to request a waiver for the GMAT/GRE requirement.
Most universities consider the overall profile of a candidate for admission to their Master’s in Data Analytics. For instance, if a university offers particular tracks, and you haven’t made the cut for your chosen track, they might offer you another, instead of rejecting your application outright.
In the next section, we’ll look at scholarships to study an MS in Data Analytics.
Scholarships to study an MS in Data Analytics
For Indian students looking to pursue an MS in Business Analytics abroad, several highly competitive scholarship opportunities are available.
Here are some notable scholarships to apply for.
| Source | Scholarship Type | Details |
| Inlaks Shivdasani Foundation | Overseas Scholarships | Offers scholarships to young Indians for full-time Master’s, MPhil, or Doctorate programs at top global institutions. |
| J. N. Tata Endowment | Loan Scholarships | Provides loan scholarships for Indian students undertaking postgraduate studies abroad. |
| Tata Trusts | Merit and Need-Based | Supports Indian students pursuing higher education both in India and internationally with scholarships. |
| Government of India | Various | Indian students can access a range of scholarships offered by various Indian government ministries and bodies. |
| British Council | GREAT Scholarships | In partnership with UK universities, it offers scholarships to Indian students for postgraduate courses in the UK. |
While external scholarships and grants are available, the most convenient way to secure financial aid for your MS in Data Analytics may be through the university you’re applying to. Many universities automatically consider all applicants for eligible scholarships, streamlining the process and increasing your chances of receiving funding.
A high number of universities also have their own scholarship/ financial aid programs. A few examples of these are given below.
| University | Type of Financial Support | Details |
| MIT Sloan | Fellowships and Assistantships | Admitted students may receive fellowships and assistantships based on academic excellence and professional promise. All admitted candidates are considered without a separate application. |
| Carnegie Mellon College of Engineering | Fellowships, Assistantships, and Work-Study | Offers full-tuition fellowships, research or teaching assistantships, and federal work-study options. Support options are department-specific and aimed at both Master’s and Ph.D. students. |
| Harvard University | Fellowships and Financial Aid | Provides a variety of fellowships and financial aid packages, often based on merit and need. Students should explore options via the university’s financial aid office. |
| Princeton University | Fellowships and Assistantships | Offers generous fellowships and assistantships to graduate students, which cover tuition and include stipends. All graduate students are automatically considered for available support. |
| University of Washington | Fellowships, Assistantships, and Financial Aid | Provides funding through fellowships, teaching assistantships, research assistantships, and other financial aid resources. Department-specific options are available for qualified applicants. |
Additionally, remember that you always have the option to take on a part-time job during your degree. Even at minimum wage, part-time work can significantly reduce your financial burden.
Note: Scholarships are great to reduce your financial burden. However, most students still need education loans to cover the rest of their expenses. When you find the best education loan, you can save significantly. FundRight helps you achieve this. Create a free profile, and get loan offers from over 15 top lenders. Upload your documents online and receive your loan disbursement quickly. With expert assistance at every step, securing a loan has never been easier.
Career scope of data analytics
Demand for advanced data analysis skills is rising across various industries. Here’s where MS in Data Analytics graduates often find work.
- Technology Sector
Data analysts in this sector work with tech companies, with a focus on product development, user experience, or operational improvements. They analyze data to enhance software solutions or streamline tech processes.
- Healthcare
In healthcare, data analysts help in managing and interpreting health data. They might work on projects that aim to improve patient outcomes, streamline hospital operations, or contribute to public health research.
- Finance
Financial institutions employ data analysts to manage risk, detect fraud, optimize investments, or understand consumer behavior better. They often analyze financial data to help make investment decisions or improve service delivery.
- Retail
Retail companies use data analysts to understand customer behavior, optimize inventory levels, and enhance the overall shopping experience. Analysts help in predicting trends, planning marketing strategies, and improving sales performance.
- Consulting
Many data analysts also find work in consulting firms. There, they give expert advice to various industries on how to use data for business growth and efficiency.
We should also mention here that the MS in Data Analytics is a STEM- program (if done full-time) in the USA. This means that international students can work in the USA for up to 36 months after graduating. They can work for 12 months in any case, after their F-1 visa ends, but if they graduate from a STEM program, that can be extended to 36 months.
Top recruiters for an MS in Data Analytics
Here are some of the top companies that actively recruit MS in Data Analytics graduates, segmented by industry.
- Technology and E-commerce
Leading technology companies such as Google, Microsoft, and IBM offer numerous opportunities for data analysts in areas such as product development, customer analytics, and operational efficiency. In e-commerce, giants like Amazon and Alibaba use data analytics for supply chain management, customer behavior analysis, and product recommendations.
- Healthcare
Major healthcare providers and pharmaceutical companies like Kaiser Permanente, Mayo Clinic, and Merck hire data analysts. They work to improve patient care delivery, manage clinical trials, and analyze medical data for research and development.
- Finance
Financial institutions like American Express, Citibank, and Goldman Sachs seek data analytics graduates. They work in risk assessment, fraud detection, customer data analysis, and financial forecasting.
- Retail
Retail leaders such as Walmart, Target, and Nordstrom rely on data analysts to enhance customer experience. Common work includes optimizing pricing strategies, managing inventory, and analyzing market trends to boost sales.
- Consulting
Consulting firms including Deloitte, PwC, and Accenture hire data analytics graduates. They provide expert advice and analytics services to clients across all industries, helping them to use data for strategic decision-making.
Job prospects and salaries offered after studying an MS in Data Analytics
Here is the comprehensive data for the most common roles that MS in Data Analytics graduates find themselves in. The salary data has been sourced from Glassdoor.
| Role | Average Salary |
| Data Analyst | $65,112 |
| Data Scientist | $98,789 |
| Machine Learning Engineer | $113,892 |
| Business Intelligence Analyst | $72,106 |
| Financial Analyst | $73,135 |
| Marketing Analytics Manager | $112,942 |
| Quantitative Analyst | $144,349 |
| Chief Data Officer (CDO) | $180,458 |
| Data Architect | $127,732 |
| Market Research Analyst | $63,120 |
| Overall Average | ~$105,000 |
Note: bear in mind that a lot of the students who choose to pursue an MS in Data analytics already have a few years of experience under their belt. For fresh graduates, the average salary, as we mentioned at the beginning, is about $86,000.
Frequently asked questions
- What programming languages are essential for an MS in Data Analytics?
Proficiency in Python and R is crucial. SQL and knowledge of big data tools like Hadoop and Spark are also beneficial.
- How long does it typically take to complete an MS in Data Analytics?
Most programs take 1 to 2 years to complete, depending on whether you study full-time or part-time.
- What is the difference between Data Analytics and Data Science?
Data Analytics focuses on interpreting existing data to make informed decisions. Data Science involves creating algorithms to predict future trends and behaviors.
- Can I pursue an MS in Data Analytics with a non-technical bachelor’s degree?
Yes, but you may need to take prerequisite courses in statistics, programming, and mathematics to meet admission requirements.
- Is work experience required for admission into an MS in Data Analytics program?
While not always required, relevant work experience can strengthen your application and may sometimes be a substitute for standardized test scores.
