Marian University

What you'll study

This programme combines theoretical foundations in quantitative methods with practical training in data analysis and decision support. Core topics typically include mathematical modelling, optimisation and operations research, applied statistics and econometrics, forecasting and time series analysis, simulation methods, and decision analysis. Students also study applied data techniques such as multivariate analysis, machine learning fundamentals, programming for analytics (commonly Python or R), and database/query skills.

Study is organised around a mix of coursework, hands-on lab work and a culminating applied project or capstone. Typical components are:

• Core modules in quantitative methods, optimisation and statistical inference
• Electives allowing specialisation in areas such as supply chain analytics, financial modelling, healthcare analytics or predictive modelling
• Practical workshops on programming, data visualisation and use of analytical software
• A capstone consultancy project or thesis that applies techniques to a real organisational problem, often in partnership with local employers

Entry requirements

Applicants are normally expected to hold a bachelor’s degree from an accredited institution. A degree in business, economics, mathematics, statistics, engineering, computer science or a related discipline is usually preferred because of the quantitative content of the programme. Admissions typically take into account the applicant’s undergraduate transcript, a personal statement outlining motivations and relevant experience, and one or two academic or professional references.

Practical requirements commonly include demonstrated competence in college-level mathematics (calculus and linear algebra) and basic statistics. Where applicants lack formal quantitative preparation, conditional entry or bridging modules may be offered. Some applicants may choose to submit standardised test scores (for example GRE or GMAT) to strengthen their application, especially if other parts of the record are limited. International applicants will need to provide evidence of English language proficiency if their prior education was not in English.

Career prospects

Graduates of this programme enter a wide range of data- and decision-focused roles across the private and public sectors. Typical job titles include:

• Operations research analyst / operations analyst
• Business analyst or management consultant
• Data analyst or junior data scientist
• Supply chain or logistics analyst
• Financial modeller or risk analyst

The skill set is also well suited to organisations that require optimisation and forecasting expertise—manufacturing, healthcare systems, transportation, finance and government agencies. Graduates may also continue to doctoral study in management science, operational research or related fields.

Why study at Marian University

Marian University offers small class sizes and close faculty supervision, which helps students tackle technically demanding material and secure applied project placements. The university’s location provides access to regional employers and internships, enabling students to build industry experience alongside their academic work. The programme emphasises applied learning—students gain hands-on experience with statistical software, programming tools and real-world datasets, and typically complete a capstone project that develops consultancy-style deliverables.

Students benefit from career support services, faculty with practitioner experience, and a campus culture that values collaborative learning and ethical decision-making, preparing graduates to apply quantitative skills in organisational settings responsibly and effectively.