Data Science

No separate portfolio is listed as a required component for Columbia Engineering's MS application for Data Science. However, relevant projects, research, publications, and hands-on technical work can still strengthen the case for fit when reflected through the resume/CV, optional publications, and the statement. The program itself emphasizes research and capstone-style applied work, so evidence of substantive data-science work is useful even without a formal portfolio submission.

The personal statement is a required application component. Columbia says it should explain past experiences, personal and professional growth, distinct qualities and commitment, preparation for advanced study, reasons for interest in the program, relevant experience, and post-graduation goals. This makes the statement an important way to demonstrate program fit and motivation in the holistic review.

Academics are central. Columbia Engineering states applicants are admitted only if the undergraduate record shows promise for productive and effective graduate work, and that decisions consider prior studies, record quality, and evidence of fitness for professional work. The MS admissions FAQ also expects undergraduate preparation in computer science or a related discipline, or substantial foundational CS and math coursework if the degree is from another field.

This dimension matters, but unevenly. The GRE General Test is optional for the 2026 admission cycle and Columbia states applicants who do not submit GRE scores will not be penalized. In contrast, English-language proficiency scores are required for many applicants whose undergraduate degree was earned outside designated English-speaking countries, so test scores can be mandatory for international applicants even though the main entrance test is optional.