Distinguish the three disciplines by their main focus
Statistics is the science of collecting, analysing and interpreting data. It emphasizes probabilistic models, inference and the rigorous treatment of uncertainty. Computer science studies algorithms, systems and programming. It emphasizes building software and computational efficiency. Data science is a newer field at the intersection of the two: it combines statistics, programming and knowledge of an application domain.
A data science program may resemble statistics with a programming focus or computer science with an analytical focus. To compare programs, you need to read the curriculum: how many courses are there in probability, algorithms, databases, machine learning and team projects?
Program titles therefore do not guarantee content. Two degrees with the same name may prepare students for different careers.
Read the BLS projections for data scientists
The Bureau of Labor Statistics (BLS) projects 35% employment growth for data scientists between 2025 and 2035, classified as much faster than average. The median salary was US$120,230 in May 2025, and employment reached 275,600 jobs in 2025. The BLS lists a bachelor's degree as the typical entry-level education.
A high percentage can start from a relatively modest employment base; here, 275,600 jobs represent a medium-sized occupation. Growth describes the pace, not the number of job openings a particular graduate will find. Data scientist positions are also often advertised with demanding requirements, including master's degrees; however, the BLS lists a bachelor's degree as the typical entry-level education, and the gap between the two is worth checking in job postings for the target region.
The BLS also specifies that the median salary of US$120,230 is for May 2025. It does not tell us how much a graduate earns in their first year, or which sector—finance, health care, retail or public administration—has the strongest demand. For these questions, university career services sometimes publish data that are more useful than national statistics.
Compare with software development
For software developers, quality assurance analysts and testers combined, the BLS projects 10% growth over the same period, with a median salary of US$134,040 in May 2025. The BLS describes this growth as much faster than average.
Growth is therefore lower in percentage terms than for data scientists, but the category is much larger and the median salary is higher. Percentages cannot be compared without considering the size of the category.
The BLS indicates that software developers generally come from computer science or related fields such as engineering and mathematics. Computer science therefore remains the broadest entry route: it opens doors to both development and, with additional courses, data work.
Summarize the data in a table
The following table brings together the figures cited for the United States. It does not replace statistics for the country where you intend to work.
| Occupation (United States) | Growth 2025-2035 | Median salary, May 2025 | Typical entry-level education |
|---|---|---|---|
| Data scientist | 35% | US$120,230 | Bachelor's degree |
| Software developer, QA analyst and tester | 10% | US$134,040 | Bachelor's degree |
| Information security analyst | 21% | US$129,180 | Bachelor's degree |
The table brings together three categories of different sizes. Data scientists accounted for 275,600 jobs in 2025 according to the BLS; the other two categories are larger or more specialized, and their employment totals are not included here. Growth percentages therefore cannot be compared as chances of being hired: they describe the pace of change in each category, not the number of jobs a particular graduate will find there.
Check the mathematics prerequisites
All three disciplines require mathematics: linear algebra, calculus, probability and statistics. The proportions vary. Statistics requires more on the probability side, computer science on the discrete mathematics and algorithms side, and data science on both.
Before choosing, it is useful to read the list of required courses for the first two years. A student who dislikes mathematical proofs may feel uncomfortable in theoretical statistics, while a student who dislikes programming may struggle in computer science.
Each institution publishes the secondary school or college mathematics courses that count as prerequisites. International students would benefit from comparing their secondary school curriculum with these requirements before submitting an application.
The prerequisites often fall into a few groups, which each program expresses in its own way:
- differential and integral calculus, sometimes two semesters;
- linear algebra, used in machine learning;
- probability and descriptive and inferential statistics;
- some initial programming experience, sometimes not compulsory but useful.
Read the QS 2026 rankings with their limitations in mind
The QS subject rankings published on March 25, 2026 include a “Data Science and Artificial Intelligence” table that ranks 201 universities, compared with 104 in 2025. This is a relatively new table, whose pool of institutions changes significantly from one year to the next. The Massachusetts Institute of Technology ranks first and Stanford second.
This expansion of the table limits comparisons over time: an institution can fall in the rankings without having changed. The rankings also measure research and reputation more than undergraduate teaching.
An institution's computer science and data science rankings may differ because the pools being compared are not the same. For a bachelor's degree, course content, work placements and published career outcomes matter more than rank.
Choose according to your intended career
Three typical profiles emerge. For a career in software engineering or data infrastructure, computer science or software engineering is the most direct choice. For an analytical career in research, public health, insurance or economics, statistics provides a solid and recognized foundation. For a career combining analysis and programming in a specific field, data science is suitable if the program is well structured.
A combined path is possible: a major in one discipline and a minor in another. Many institutions offer this option, and it allows students to keep both doors open.
For research roles in machine learning, a doctorate is generally expected, which favours a bachelor's degree with a strong mathematics component.
Check work placements and projects
Employers look for concrete evidence: complete analytical projects, public code repositories, participation in competitions and work placements. A program that includes a paid work placement or a final-year project with a real-world partner provides such evidence.
Practical skills to develop include a widely used programming language, databases, visualization, communicating results to non-specialists and version control. Theoretical courses remain useful when tools change.
One caution: short training programs do not replace a degree in every situation, and no comparable data on their effect on hiring were found in the sources consulted.
A complete analytical project, from the initial question to the presentation of results, is worth more than a series of isolated exercises. It demonstrates the ability to clean imperfect data, choose an appropriate method and explain the limitations of a conclusion, which employers often assess during interviews.
What about Canada?
In Canada, computer science and data professions are not regulated in the same way as engineering. Employers generally require a university degree and evidence of experience. Employment statistics by occupation are published separately by federal and provincial organizations and do not correspond to the U.S. figures in this article.
StudyCanada features, among others, the statistics program at Université de Montréal, the computer science program at the University of Waterloo, the data science program at The University of British Columbia, and the computer science and data science programs at McGill University. Mathematics prerequisites and requirements for international students can be found on each program's page. Several of these universities offer co-op work placements, allowing students to present an employer with concrete experience before completing their bachelor's degree; the length and pay of work placements can be found in each program's description.