University of Saskatchewan

What you'll study

The programme combines advanced coursework with supervised research. Typical course topics include probability theory and mathematical statistics, statistical inference, linear and generalized linear models, multivariate analysis, time series, survival analysis, Bayesian methods, spatial statistics, stochastic processes and statistical computing (including extensive use of R and other scientific computing tools).

Students normally take a set of core courses to build a foundation in rigorous probability and inference, plus a selection of electives that reflect applied interests such as environmental/ecological statistics, biostatistics, machine learning, or actuarial and financial statistics. The degree is research-oriented: students complete an original thesis or an equivalent major research project under the supervision of a faculty member in the Department of Statistics and Actuarial Science.

Entry requirements

Applicants are expected to hold a four-year bachelor’s degree (or equivalent) in statistics, mathematics, or a closely related discipline, typically with substantial coursework in calculus, linear algebra, probability and mathematical statistics. A strong undergraduate record in quantitative subjects is required.

Required application materials generally include official transcripts, a statement of research interests or purpose, a curriculum vitae, and two or three academic references. International applicants must demonstrate English language proficiency to the University’s standard. Some applicants may be asked to meet with potential supervisors or submit examples of prior coursework or projects. GRE scores are not routinely required but may be submitted if available.

Career prospects

Graduates move into a wide range of roles where advanced statistical training is valued. Common career paths include data scientist or statistician in industry, biostatistician in health and clinical research, environmental and ecological modeller, government statistician or analyst, actuarial and financial analyst, and research scientist in private and public research organisations. Many students also use the Master’s as preparation for PhD study and academic careers.

Employers for graduates typically include public health agencies, provincial and federal government departments, agricultural and environmental research organisations, pharmaceutical and biotechnology firms, consulting companies, and data-driven technology businesses. Training in statistical computing and applied modelling increases employability across sectors that rely on large or complex data.

Why study at University of Saskatchewan

The University of Saskatchewan’s Department of Statistics and Actuarial Science offers focused graduate supervision within a mid-sized research university environment. Students benefit from close interaction with faculty on supervised research projects and access to computing resources and statistical software commonly used in research and industry.

The university’s research strengths and interdisciplinary collaborations create opportunities to apply statistical methods in areas like environmental science, agriculture, health research and infectious disease, often in partnership with campus research centres and provincial agencies. Funding opportunities such as research assistantships and teaching assistantships are commonly available to qualified graduate students, and the programme prepares students for both professional practice and further academic study.