Seattle University

What you'll study

This programme combines core theory in management science with practical training in quantitative methods and computing. Typical study areas include optimisation (linear and integer programming), stochastic processes and queuing theory, simulation modelling, statistical inference and applied regression, forecasting, decision analysis, and supply chain and inventory models. Students also learn programming for analytics (commonly using Python or R), database and data management fundamentals, and methods for prescriptive analytics.

The degree is normally structured around a set of core courses, a choice of electives to deepen specialisms (for example in analytics, operations, finance or healthcare systems), and an applied culminating experience such as a capstone project or practicum with an industry partner. Coursework emphasises hands-on problem solving with real datasets, building models, and communicating results to non-technical stakeholders.

Entry requirements

• A recognised undergraduate degree, typically with a strong quantitative element (for example mathematics, statistics, engineering, economics, computer science, or a related field).
• Evidence of prior quantitative coursework such as calculus, linear algebra and introductory statistics. Candidates without a formal quantitative degree may be considered if they demonstrate sufficient quantitative preparation through coursework or professional experience.
• Academic transcripts and a personal statement outlining your quantitative interests and career goals.
• Professional résumé; letters of recommendation are commonly required.
• International applicants must meet English language proficiency requirements. Standardised test scores (GRE/GMAT) may be requested in some cases but are often considered supplemental; check the programme for current testing policy.

Career prospects

Graduates move into roles that require strong analytical and decision-support skills. Common job titles include operations research analyst, data analyst, business analyst, supply chain analyst, quantitative analyst, process improvement specialist and management consultant. Employers span technology firms, logistics and transportation companies, manufacturing, healthcare systems, financial services, and consulting firms. The programme also prepares students for doctoral study in related fields by providing rigorous training in modelling and inference.

Why study at Seattle University

• Seattle University offers a personalised learning environment with small class sizes, enabling close interaction with faculty who focus on applied research and industry-relevant problems.
• The university’s location in Seattle provides proximity to a dense cluster of technology, aerospace, maritime and healthcare organisations, creating opportunities for internships, practicum projects and employer engagement.
• Emphasis on experiential learning and ethical decision making aligns technical training with leadership and communication skills needed to implement quantitative solutions in organisations.
• Students benefit from cross-disciplinary collaboration across business, engineering and computer science, preparing graduates to work effectively on multidisciplinary teams.