Top 9 Scholarships Aspiring Data Scientists Should Apply For

Data science stands out as one of the most exciting and in-demand fields in the world of technology and innovation. Aspiring data scientists, from high school students taking their first steps into STEM to graduate school applicants, career changers, and professionals seeking to pivot into data science, all share a common concern: how to fund their education.

The exceptionally high cost associated with pursuing specialized and advanced degrees in data science can often be quite daunting, creating a substantial and sometimes insurmountable barrier for many talented and motivated individuals who aspire to enter the field.

Top 9 Scholarships Aspiring Data Scientists Should Apply For

This blog post aims to bridge that gap by presenting the top 9 scholarships specifically tailored for aspiring data scientists. Each scholarship offers a financial lifeline, making the pursuit of a data science degree or advanced study more accessible.

Whether you are an undergraduate student just starting your academic journey, a graduate student advancing your education, or a non-traditional learner returning to school later in life, this carefully curated guide is designed to assist you in navigating the often complex and overwhelming world of scholarships with both confidence and clarity. It aims to provide you with the essential tools and information needed to find and secure the financial aid opportunities best suited to your unique educational path.

Table of Contents

What Are Data Science Scholarships?

Data science scholarships are financial awards specifically designed to support students pursuing education and careers in data science as well as related fields such as computer science, statistics, analytics, and artificial intelligence. These scholarships serve to ease the financial burden associated with tuition, books, housing, and other educational expenses.

They come in a wide variety of different forms and types, including but not limited to the following:

Merit-based scholarships are designed to recognize and reward outstanding academic excellence along with exceptional skills and talents demonstrated by students. These scholarships aim to encourage and support individuals who have shown remarkable achievements in their educational pursuits and various skill areas.

Need-based scholarships are specifically designed to support students who demonstrate clear financial need, providing crucial assistance to help cover the costs of their education. These scholarships aim to ensure that talented and motivated individuals have access to educational opportunities regardless of their financial background.

Targeted scholarships are specifically designed to support and encourage individuals from underrepresented groups in the technology sector, with the primary goal of promoting greater diversity and fostering a more inclusive environment within the industry. These scholarships provide vital financial assistance and opportunities, helping to break down barriers and enable talented candidates from diverse backgrounds to pursue education and careers in technology fields where they have historically been underrepresented.

In addition to financial aid, many data science scholarships offer additional benefits such as internships, mentorship programs, networking opportunities, and research experiences. This combination not only helps students fund their education but also prepares them with real-world skills and connections to advance their careers.

Such scholarships are available for a wide range of educational levels, spanning from undergraduate degrees to graduate programs and even doctoral studies. These financial awards play a crucial role in helping aspiring data scientists acquire and develop the essential competencies and skills necessary for various professional roles.

These roles include positions such as data analyst, data engineer, machine learning specialist, and many other key roles that are vital within the rapidly evolving and constantly changing data ecosystem.

Why Pursue Data Science?

Data science is a highly dynamic and interdisciplinary field that integrates statistics, advanced technology, and deep domain expertise to analyze, interpret, and extract meaningful insights from complex and large data sets. This comprehensive process enables organizations to make well-informed decisions, enhance operational efficiency, and foster innovation across a wide range of industries.

Some of the key sectors benefiting from data science include healthcare, finance, retail, and government, where data-driven strategies are transforming the way these industries operate and compete in the modern world.

The significance of pursuing a career or education in data science arises from a variety of important factors that contribute to its growing relevance and demand in today’s world:

High Demand for Skilled Professionals

Industry reports and projections consistently indicate that the demand for data scientist roles is expected to experience significant growth, approximately 35-36% from 2022 to 2032, which far outpaces the growth rates of many other professions in the job market. This increasing demand is primarily driven by organizations across various sectors becoming increasingly data-driven, relying heavily on data to inform their strategic decisions.

As a result, there is a growing need for highly skilled experts who can efficiently extract actionable insights from vast and complex datasets, enabling businesses to make smarter, evidence-based decisions and maintain a competitive edge in their industries.

Lucrative Career Opportunities

Entry-level data scientists can anticipate highly competitive salaries, typically starting in the range of $85,000 to $110,000 per year. As they gain experience and specialize in advanced fields such as machine learning and artificial intelligence, senior specialists have the potential to earn significantly higher incomes.

This attractive financial incentive, combined with the strong job stability and growing demand for skilled professionals in the industry, makes data science a particularly rewarding and promising career path for many individuals.

Diverse Skill Set Development

Studying data science encourages the growth of a unique and versatile blend of skills, including a strong attention to detail, advanced analytical thinking, proficient programming abilities, creative innovation, effective problem-solving strategies, and clear communication.

These competencies are not only essential within the field of data science but are also highly transferable and valuable across a broad range of job roles and industries, enhancing career flexibility and opportunities far beyond data science alone.

Driving Innovation and Making Better Decisions

Data science empowers businesses to uncover emerging trends, enhance and streamline their operational processes, effectively manage various risks, and develop innovative products or services. This capability is essential for companies striving to maintain and improve their competitiveness in today’s rapidly changing and highly dynamic markets.

Long-Term Career Growth

The field is constantly and rapidly evolving with the introduction of cutting-edge technologies such as artificial intelligence and machine learning. These advancements create abundant opportunities for lifelong learning and continuous professional development.

Motivated and dedicated individuals who maintain a strong sense of curiosity and consistently adopt a proactive approach can experience substantial career advancement and enjoy long-term professional growth in this dynamic, fast-paced, and ever-evolving industry. By staying engaged and continuously seeking new knowledge and opportunities, they position themselves for ongoing success and development.

In Summary

Pursuing a career in data science positions students and professionals right at the crossroads of the most advanced cutting-edge technology and significant real-world impact, providing access to high-paying job opportunities, robust and promising career prospects, as well as the unique chance to shape the future through data-driven innovation and insights actively.

Top Scholarships Aspiring Data Scientists Should Apply For

Below is a comprehensive and detailed list of nine highly prestigious scholarships that are specifically designed to support various stages of the data science education journey. These scholarships have been carefully selected based on multiple important factors, including their overall financial value, eligibility criteria, the specific target demographic they serve, and the significant potential career benefits they offer to recipients.

ACM SIGHPC/Intel Computational & Data Science Scholarship

Type: Graduate Scholarship
Amount: $15,000 annually for up to two years, with potential for extension.
Focus: Supports women and underrepresented minorities pursuing graduate studies in data science worldwide. This scholarship is a targeted effort to increase diversity in computational and data science fields.
Why Apply: This is a highly sought-after award that not only provides substantial financial support but also offers significant professional visibility and networking opportunities within the ACM and Intel communities.
Example: Many past recipients have leveraged this award as a stepping stone to careers at major tech firms like Google and Amazon, as well as advanced academic research roles.

Acxiom Diversity Scholarship

Type: Undergraduate/Graduate Scholarship
Amount: Varies, often paired with summer internships. The exact amount is not always published, but it is designed to significantly offset tuition costs.
Focus: Specifically targets students from underrepresented groups in information technology and data science fields. The scholarship’s core mission is to create a more inclusive tech workforce.
Why Apply: Besides financial support, scholars may get valuable industry exposure through paid internships at Acxiom, a leader in data and marketing technology. This hands-on experience can be a crucial differentiator on a resume.
Example: Successful scholars have credited this award for both financial aid and career development, often leading to a full-time job offer after graduation.

Milliman Opportunity Scholarship Fund

Type: Undergraduate Scholarship
Amount: Varies; 15–25 awards per year. The awards are typically for a minimum of $5,000.
Focus: Students from historically underrepresented groups studying data science, actuarial science, or statistics.
Why Apply: This scholarship seeks to promote diversity in quantitative fields and helps ease financial burdens for promising undergraduates. Recipients often benefit from networking opportunities with industry professionals at Milliman, a top actuarial and consulting firm.
Example: Students who demonstrate strong academic records and leadership potential in their applications have a high chance of success.

MinneAnalytics Data Science Scholarship

Type: Undergraduate Scholarship
Amount: Varies; awards are typically for $1,000.
Focus: Awards students committed to community service and engagement in data science. The scholarship is aimed at students attending colleges and universities in the Midwest, particularly in Minnesota.
Why Apply: This scholarship encourages a community-minded approach to data science education and supports applicants demonstrating leadership outside academia. It’s an excellent opportunity for students who are active in tech-related community initiatives.
Example: Students who are part of a student-run data club or have volunteered to analyze data for a non-profit organization are strong candidates.

Department of Energy Computational Science Graduate Fellowship (DOE CSGF)

Type: Graduate Fellowship
Amount: $45,000 yearly stipend for up to four years, plus full tuition and fees.
Focus: Broadly supports students in computational sciences, including data science at U.S. institutions. It is one of the most generous and prestigious fellowships available.
Why Apply: The fellowship offers a handsome stipend, full tuition, and a required 12-week research internship at a U.S. national lab. This is perfect for students interested in the scientific applications of data science, such as climate modeling or materials science.
Example: Scholars often publish cutting-edge research and build careers in government, academia, or private industry with a focus on R&D.

University of Birmingham AI and Data Science Master’s Scholarship

Type: Postgraduate Scholarship (UK)
Amount: £10,000, awarded as a fee waiver.
Focus: Supports students from underrepresented groups (women, Black, disabled, and low socioeconomic backgrounds) in master’s programs related to AI and data science at the University of Birmingham.
Why Apply: Funded by UK government bodies, it promotes inclusivity in technology sectors and offers substantial tuition relief for a master’s degree. It’s a key opportunity for students aiming for a career in the European tech market.
Example: This scholarship is part of a larger initiative to address the diversity gap in the UK tech industry. Over 100 students have benefited from this program, smoothing their path to tech careers in Europe.

University of Washington Master of Science in Data Science (MSDS) Scholarships and Funding

Type: Partial Scholarships and Work-Study
Amount: Varies, from partial tuition scholarships to up to $5,000 annually for work-study programs.
Focus: Graduate students enrolled in the MSDS program are automatically considered for these merit scholarships; additional work-study options are available. The program is specifically for students admitted to the University of Washington’s program.
Why Apply: Offers a blend of scholarship and paid on-campus work to support graduate studies. It’s a good option for students who want to reduce debt and gain practical, on-campus experience.
Example: Students who balance scholarship awards with work-study often gain hands-on experience in a research lab or administrative department, which can be as valuable as the financial aid.

NYU Center for Data Science Scholarships

Type: Graduate Scholarships
Amount: Can cover full tuition for select MS students.
Focus: Highly competitive tuition scholarships for outstanding students in NYU’s pioneering data science master’s program. The scholarships are often merit-based or tied to specific initiatives (like the Google DeepMind Scholarship) that aim to increase diversity and support talented students.
Why Apply: Full tuition coverage plus access to NYU’s urban tech ecosystem is a significant advantage, ideal for students seeking a career launchpad in a major tech hub like New York City.
Example: Recipients gain mentorship from NYU’s expert faculty and industry partners, and the prestige of the award can open many doors.

Remote DBA Experts to Students Scholarship

Type: Undergraduate and Graduate Scholarship
Amount: Varies; often $1,000.
Focus: Students with a GPA above 2.5 in data science or related fields. The scholarship is open to students worldwide.
Why Apply: This award offers a straightforward and accessible opportunity to receive funding from a specialized data services company. The lower GPA requirement makes it an excellent option for students who might have other strengths, like practical experience or a compelling essay.
Example: The scholarship typically requires an essay on a data-related topic, allowing students to showcase their passion and vision for the field. It’s a good way to earn a scholarship for students who may not have a perfect academic record but have a clear career vision.

Why Apply for Data Science Scholarships?

Data science has rapidly become one of the fastest-growing and highest-paying career fields in today’s job market, attracting a great deal of interest from aspiring professionals. However, the cost of obtaining a quality education, especially at the graduate level, often presents a significant financial obstacle that many find difficult to overcome.

Scholarships specifically targeted toward data science students offer far more than just financial assistance; they represent a strategic investment in your long-term career and personal growth. By diligently applying for and securing these scholarships, you can gain access to a wide array of valuable benefits that extend well beyond merely alleviating the burden of tuition fees.

Overcome Financial Barriers

The most obvious and immediate benefit of receiving a scholarship is the significant positive impact it has on your overall finances. Scholarships provide crucial financial support that directly addresses the often overwhelming high costs associated with specialized education.

These expenses can encompass a wide range of necessities such as tuition fees, textbooks, living costs, as well as the purchase of expensive software or hardware required for your studies. By successfully securing scholarship funding, you gain the ability to:

Reduce Student Loan Debt: A scholarship is “free money” that you don’t have to pay back. This can drastically reduce the amount of debt you accumulate, giving you greater financial freedom after graduation.
Focus on Academics: Without the pressure of balancing multiple jobs to pay for school, you can dedicate more time and energy to your studies, research, and projects. This can lead to better grades and a more in-depth understanding of complex topics.

Accelerate Your Career

Many data science scholarships are often connected to particular companies or organizations, and they serve purposes beyond merely offering financial support. These scholarships are frequently designed to act as a talent pipeline, helping to identify and nurture the most promising individuals in the field. Securing a scholarship can offer a range of valuable benefits, including:

Valuable Internships and Job Opportunities: As seen with scholarships from companies like Acxiom and Bloomberg, many awards come with guaranteed or preferred consideration for internships. These paid, hands-on experiences can give you a significant advantage in the job market and often lead to full-time employment.
Mentorship and Networking: Scholarship sponsors often provide access to their professional networks and offer mentorship from industry experts. This can give you invaluable insights into the real-world applications of data science and connect you with people who can help shape your career path.
A Competitive Edge: Listing a prestigious scholarship on your resume or LinkedIn profile is a powerful signal to employers. It proves that a respected organization has vetted your skills, potential, and drive. This can make you stand out from other candidates.

Support a More Diverse Future

Many of the scholarships featured on this list, including well-known opportunities like the ACM SIGHPC/Intel Scholarship and the Milliman Opportunity Scholarship, are specifically created to support and uplift underrepresented groups within the field.

When you apply for these scholarships, you are doing more than just advancing your own educational and professional goals—you are actively contributing to the creation of a more inclusive, diverse, and representative data science community.

Research and experience have shown that a diverse workforce brings a wider range of perspectives, which leads to greater innovation and improved problem-solving abilities when tackling complex challenges. By taking part in these scholarship programs, you are helping to build a stronger, more equitable future for the entire data science profession.

In a field as dynamic, fast-evolving, and highly competitive as data science, securing scholarship funding can dramatically accelerate both your educational journey and your long-term career success. Pursuing such financial support is a highly strategic and wise decision that offers not only a solid financial foundation to ease the burden of tuition and related expenses but also invaluable opportunities to build your professional network, gain real-world experience, and participate in cutting-edge projects.

Moreover, obtaining a scholarship offers an exceptional opportunity to make a meaningful and lasting impact on the rapidly advancing and ever-evolving field of data science. This valuable support not only enhances your knowledge and skills but also helps you distinguish yourself as a future leader and innovative thinker in the industry, opening doors to numerous exciting possibilities and career advancements.

Current Trends in Data Science Education Funding

Current trends in data science education funding reveal a dynamic and increasingly inclusive landscape that is specifically designed to foster innovation, promote diversity, and develop practical skills among learners.

These emerging trends are significantly shaping the way scholarships and various financial aid opportunities are evolving, with a strong focus on supporting and empowering the next generation of skilled data scientists across different backgrounds and regions.

Increased Diversity Support

One of the most prominent trends is the emphasis on promoting diversity and inclusion within the field. Scholarship programs are increasingly targeting women, underrepresented minorities, and students from economically disadvantaged backgrounds to address the gender gap and racial disparities in tech and data science.

Initiatives like the ACM SIGHPC/Intel Scholarship and UK-based programs from the University of Birmingham exemplify this focus, helping historically underserved groups access quality education and research opportunities. This movement not only fosters a more equitable tech ecosystem but also enriches the field with diverse perspectives, leading to innovative solutions.

Growing Global Opportunities

Data science’s importance is recognized worldwide, and many scholarship programs now welcome international students. This global approach reflects the universal demand for data science skills and promotes cross-cultural collaboration.

Scholarships like those offered by universities in the UK, Switzerland, and the US are expanding access to students regardless of their geographic location. This trend promotes equity and talent mobility, enabling bright minds from developing countries to contribute to global data science advancements.

Integration of Work and Internships

Many scholarships today are bundled with practical work experience—through internships, apprenticeships, or research positions. This integration provides students with hands-on exposure to real-world applications of data science, thereby boosting employability upon graduation.

For example, the Department of Energy’s Computational Science Graduate Fellowship includes internships at national labs, while university-specific programs like those at Washington and NYU combine funding with paid research or industry experience. This approach ensures students gain both financial support and valuable professional skills.

Growth of AI and Interdisciplinary Scholarships

As AI, machine learning, and interdisciplinary data science fields continue to expand, scholarship programs are broadening their scope. Many funding opportunities now specifically support AI-focused master’s and doctoral programs, emphasizing the importance of interdisciplinary skills that combine domain expertise with advanced data techniques.

These scholarships actively foster innovation and creative thinking in a wide range of fields such as health technology, financial services, and environmental science. They are designed to encourage and inspire students to develop innovative solutions that go beyond and cross traditional academic boundaries and disciplines. This approach nurtures interdisciplinary collaboration and helps students tackle complex problems with fresh perspectives and cutting-edge ideas.

In Summary

These current and emerging trends in data science education funding clearly demonstrate a strong and ongoing commitment to fostering a more inclusive, globally connected, and practically oriented field.

As scholarships and grants increasingly prioritize support for diversity, encourage international participation, and promote work-based learning experiences—particularly in cutting-edge areas such as artificial intelligence and interdisciplinary domains—the range of opportunities available for aspiring data scientists to advance their careers expands significantly.

By staying informed and aware of these evolving trends, both students and educators can better position themselves to take advantage of new and diverse funding opportunities, ultimately driving sustained growth, innovation, and excellence within the rapidly evolving field of data science.

FAQs

Can non-traditional students apply for data science scholarships?

Many scholarships specifically accommodate career changers and professionals seeking degrees or certifications in data science, including bootcamps. Look for scholarships mentioning eligibility for non-traditional students or those with prior work experience. Several programs also accept candidates from different academic backgrounds as long as they demonstrate interest and aptitude in data science.

Are there scholarships specifically for undergraduate students interested in data science?

Scholarships like the Milliman Opportunity Scholarship and MinneAnalytics Data Science Scholarship are designed for undergraduates, often prioritizing underrepresented groups and academic excellence. Other scholarships frequently require a minimum GPA, typically around 2.5 or higher.

Do graduate data science programs offer scholarships automatically?

Some programs, such as the University of Washington’s MSDS, consider admitted students automatically for merit scholarships or work-study funding without a separate application. However, most scholarships, especially prestigious or external awards, require distinct applications and documentation.

How competitive are data science scholarships?

Competitiveness varies widely. Prestigious scholarships like the NYU Center for Data Science awards or DOE Computational Science Fellowship are highly competitive, requiring excellent academic records, strong recommendations, and sometimes research proposals. Others have broader or diversity-focused criteria and may be less competitive.

Is it possible to combine multiple scholarships?

Students can often combine scholarships, grants, and work-study programs to cover tuition and living costs. However, some scholarships have restrictions about stacking with full scholarships or employer-funded sponsorships. It’s critical to review each award’s terms and conditions before accepting multiple scholarships.

In Conclusion

Pursuing a career in data science is a wise investment given the field’s dynamic growth and lucrative opportunities. However, the cost of education can be a hurdle. Fortunately, numerous scholarships exist to support aspiring data scientists at all career stages—from high school and undergraduate students to graduate applicants and mid-career professionals.

Applying for the scholarships listed here can significantly ease financial burdens while opening doors to career-building experiences like internships, mentorships, and networking. It is recommended to start early, prepare strong applications, and seek scholarships aligned with one’s background and goals.

For students and professionals navigating this challenging and rewarding journey, these scholarships do much more than simply provide financial support for education. They play a crucial role in empowering the next generation of data scientists, equipping them with the resources and confidence needed to innovate, lead, and make significant contributions in their fields.