Master of Science in Data Science

Highlights

The Master of Science in Data Science (MScDS) is normally a 2-year program. The goal of the program is to provide students with solid knowledge, techniques, and experience in the research and application of data science, and to prepare students to become researchers and leaders in the emerging area of data science at the regional, national, and global levels.

The program is unique in that it can be an application-orientated or a research-orientated master’s program depending on whether students choose the Graduate Project option or the Graduate Thesis option. Regardless of their choice, graduates will develop the strong data analytics, critical-thinking, communication, and interpersonal skills required for success as a data scientist in big data or to pursue further advances in research.

Careers

The demand for people with data analytics skills is very high at the present and will be even greater in the near future. In a general sense, it is estimated by Canada’s Big Data Consortium that in 2018 Canada’s overall shortage of professionals with deep analytical skills will be in the range of 14,000 to 19,000, and shortage of data literate managers and analysts will be about 150,000. The shortfall is not fulfilled yet at this day and the demand gap grows even larger.

These opportunities for graduates are in the areas of:

• Data scientists in large private or public organizations
• Data analyst positions in
  • software development
  • business intelligence
  • medical/health research
  • data management
• Strategic analysis manager positions of policy making bodies of government and organizations
• Data architect designers of social networks, communication networks and the like

Admission Requirements

• Acceptable four (4) year bachelor degree or equivalent in a discipline of science, or a related discipline with a minimum average grade in the last 60 credits of:

  • B (GPA of 3.00 on a scale of 4.33) for project option;
  • B+ (GPA of 3.33 on a scale of 4.33) for thesis option.
  
  

  Preference will be given to students who have specialized in the areas of Statistics, Computing Science, Mathematics and Engineering.

• Prospective students are expected to demonstrate working knowledge of statistics, data structures and algorithms, databases and R/Python software packages. Examples of course work that demonstrates such knowledge at Thompson Rivers University are MATH 2110 (Calculus III), MATH 2120 (Linear Algebra), STAT 2000 (Introduction to Statistics) and COMP 1231 (Computer Programming II).

• Applicants who did not complete their undergraduate degree in an English language university in a country whose first language is English must have one of the following:

  • a minimum TOEFL score of 570 with a TWE of 4.5 or higher, or
  • a minimum iBT score of 88 with no section below 20, or
  • IELTS of at least 6.5 with no band below 6.0, or
  • CAEL of at least 70 with no subsets below 60.

• Two letters of reference** from academics or professionals. Letters should comment on the applicant’s academic ability and record, training, research/work experience, in particular relating to statistics, programming, data analysis, machine learning, or AI.

• Official academic transcript(s)** from all prior post-secondary institutions attended.

** Note: Required supporting documents must be sent directly to Thompson Rivers University from the referee or institution.

Admission to the Master of Science in Data Science program will be determined by candidate’s academic and professional record, letters of recommendation, areas of research interest and the ability of the faculty member to accept the student into their research group.

Students who do not meet the admission requirement may be required to take prerequisite courses. The admission subcommittee in consultation with the program coordinator would determine the courses that would need to be taken to meet the admission requirements.

Tuition

Next Steps

Apply to this program Visit the program website