Saint Mary’s University of Minnesota

What you'll study

This programme combines statistics, operations research and applied analytics to prepare students to model and solve complex business problems. Core topics typically include statistical inference and regression, forecasting, optimisation and linear programming, simulation modelling, decision analysis, and multivariate techniques. Students also study data management and analytics tools such as programming for data science (Python or R), database querying, and data visualisation.

Study is usually delivered through a mix of taught modules and a culminating applied project or practicum. Typical modules and subjects you can expect:

• Statistical Methods for Management – probability, estimation, hypothesis testing, and regression models.
• Forecasting and Time Series Analysis – short- and long-term forecasting techniques and model evaluation.
• Optimisation and Operations Research – linear and integer programming, network models and sensitivity analysis.
• Simulation and Risk Analysis – Monte Carlo simulation, queuing and stochastic modelling for operational decisions.
• Data Mining and Machine Learning for Business – classification, clustering and predictive modelling tailored to business applications.
• Decision Analysis and Managerial Economics – decision trees, utility theory and incorporating economics into managerial decisions.
• Programming and Data Management – practical skills in data wrangling, SQL, and scripting for analysis in R or Python.
• Applied Capstone or Practicum – a real-world project with a corporate partner, public agency or substantial dataset to demonstrate applied problem-solving.

The programme emphasises applied coursework, case studies and project-based assessment so graduates can translate quantitative outputs into actionable business recommendations.

Entry requirements

Applicants are expected to hold a recognised bachelor’s degree. Candidates with degrees in business, economics, mathematics, engineering, computer science or related disciplines are particularly well placed. If your undergraduate degree is in a non-quantitative subject you may be asked to show evidence of quantitative aptitude through prior coursework or professional experience.

Typical admissions materials include a completed application, academic transcripts, a personal statement outlining objectives and quantitative experience, and one or more references. Relevant professional experience is valued and may strengthen an application. The programme may accept applicants without standardised test scores, though some applicants choose to submit GRE or similar results if they wish to demonstrate quantitative readiness.

Career prospects

Graduates move into analytical and decision-support roles across private and public sectors. Common job titles and pathways include:

• Data analyst or data scientist in sectors such as finance, healthcare, retail and manufacturing.
• Operations or supply chain analyst focused on optimisation, inventory planning and process improvement.
• Business intelligence analyst or reporting specialist producing dashboards and management reports.
• Risk analyst or actuarial support roles assessing financial and operational risk.
• Management consultant specialising in performance improvement and data-driven strategy.
• Progression to leadership roles that require sound quantitative judgement, or further academic study (e.g. PhD in related fields) for those interested in research careers.

Because the programme stresses applied methods and communication of results, graduates are equipped to bridge technical teams and senior managers.

Why study at Saint Mary’s University of Minnesota

Saint Mary’s University of Minnesota combines a student-centred environment with applied, career-focused graduate education. The university’s smaller class sizes allow for close interaction with faculty who bring a mix of academic expertise and industry experience. The programme’s applied capstone/practicum connects students with regional employers and projects, helping to build a professional portfolio.

Students benefit from flexible delivery formats that accommodate working professionals, and from career support services that help with internship and job placement opportunities. The university’s Lasallian tradition emphasises ethical leadership and service, preparing graduates to apply quantitative skills with an awareness of organisational and social contexts. Proximity to the Twin Cities business community expands networking and internship options for students seeking regional industry experience.