PhD Degree in Data Science & Analytics - About Minimum Qualification, Universities, And Admission 2025-26

About This Course

The Doctor of Philosophy (Ph.D.) program in Data Science, Analytics, and Engineering is designed for ambitious scholars who want to push the boundaries of data-driven research and create meaningful impact on society. This doctoral program deeply engages students in both fundamental and applied research, equipping them with the expertise required to tackle complex, real-world problems using advanced data science methodologies.

At its core, the program focuses on developing the ability to conduct original, high-quality research. Students are trained to identify emerging research gaps, critically evaluate existing analytical approaches, and adapt or design innovative data-driven methods when current solutions fall short. Through a rigorous combination of coursework, research projects, and academic mentorship, doctoral candidates gain the intellectual independence needed to contribute new knowledge to the field of data science and analytics.

The Ph.D. in Business Analytics and Data Science is particularly suited for experienced professionals aiming for senior leadership roles in public institutions, private enterprises, or global organizations. The program emphasizes a strong understanding of decision sciences and the strategic use of analytics technologies from institutional, industry, and international perspectives. Students develop advanced critical thinking, leadership, and technical decision science skills, enabling them to make informed, high-impact decisions at the highest levels of management and policy.

Supported by the School of Data Science at the University of Virginia, the Ph.D. in Data Science offers a rich academic environment focused on research excellence and interdisciplinary collaboration. Doctoral students master the computational and mathematical foundations of data science while gaining hands-on expertise in data engineering, software development, data policy, and ethics. With a strong balance of theory and application, this program prepares graduates to become influential data science leaders, researchers, and innovators in an increasingly data-driven world.

Eligibility

Candidates applying for the program must meet the prescribed minimum academic eligibility criteria to be considered for admission. Applicants should have secured at least 60% marks in aggregate, or an equivalent CGPA on a 10-point grading scale, in either a Master’s degree or a four-year Bachelor’s degree such as BE, BTech, BS, or an equivalent qualification.

The qualifying degree should be in Data Science, Mathematics, Statistics, Computer Science, or any other science or engineering discipline from a recognized university or institution. This academic requirement ensures that candidates possess a strong foundational background necessary to pursue advanced research and coursework in data science, analytics, and related interdisciplinary areas.

For candidates belonging to Scheduled Caste (SC), Scheduled Tribe (ST), and Persons with Disabilities (PD/VH) categories, the eligibility criteria are relaxed in accordance with applicable reservation norms. Such applicants are required to have a minimum of 55% marks in aggregate, or an equivalent CGPA, in their qualifying degree.

Meeting the minimum eligibility criteria does not automatically guarantee admission, as selection may also depend on additional factors such as entrance examinations, interviews, research aptitude, and institutional guidelines. Applicants are advised to carefully review the eligibility requirements and ensure that their academic qualifications align with the program’s expectations before applying.

PhD Degree in Data Science & Analytics Admission Process

All prospective students must satisfy the general admission standards set by the university, regardless of whether they are applying from the U.S. or internationally. In addition to these baseline criteria, applicants are required to meet the specific academic and documentation requirements established by both the Graduate College and the Ira A. Fulton Schools of Engineering. These dual standards ensure that candidates are well-prepared for the academic rigor and research-focused environment of the program.

The program welcomes applications from individuals who hold either a bachelor’s or a master’s degree in engineering, computer science, mathematics, statistics, or a closely related discipline. Degrees must be awarded by a regionally accredited institution, reflecting a solid academic foundation relevant to advanced graduate-level study.

Academic performance plays a key role in the evaluation process. Applicants are expected to demonstrate strong scholastic achievement with a minimum cumulative GPA of 3.00 on a 4.00 scale. This requirement applies to the last 60 credit hours of the applicant’s first bachelor’s degree or, alternatively, to an applicable master’s degree program. Meeting this benchmark indicates the applicant’s readiness to succeed in a demanding academic setting.

To complete the application, candidates must submit a comprehensive set of materials. These include a completed graduate admission application along with the required application fee, official academic transcripts from all previously attended institutions, and two letters of recommendation that speak to the applicant’s academic ability and potential. A letter of intent or written statement is also required, allowing applicants to clearly articulate their goals, interests, and motivation for pursuing the program. Additionally, GRE scores must be provided as part of the evaluation process.

Future Scope

Powered by data, today’s world is being transformed in remarkable ways—from smarter healthcare systems to more efficient financial decision-making. Whether you are beginning your journey in data science or aiming to advance into a leadership role, this program offers a clear pathway into one of the fastest-growing and most in-demand fields globally.

The University of Calgary’s Professional Graduate Program in Data Science and Analytics is designed to equip you with practical, industry-relevant skills. Through hands-on learning, you will gain experience working with real-world data sets, applying analytical techniques, and making informed, data-driven decisions. The program also emphasizes data visualization and the strategic use of business insight, enabling you to communicate findings effectively and solve complex problems with confidence.

By combining technical expertise with analytical thinking and business acumen, this program prepares you to turn data into meaningful impact and position yourself for long-term career growth in a data-driven economy.