Susquehanna University

What you'll study

This interdisciplinary programme integrates quantitative techniques, decision science and management theory. You will study probability and statistics, linear algebra and optimisation, econometrics, simulation and forecasting, and database and programming tools commonly used in analytics (for example R and Python). Management content covers organisational behaviour, managerial economics, operations and supply-chain management, finance and marketing, giving context to quantitative problem solving.

The curriculum typically includes a sequence of core quantitative modules (statistics, mathematical modelling, operations research), foundation business courses, and elective options that allow you to focus on areas such as business analytics, finance, supply chain, or information systems. Coursework emphasises hands-on projects, case studies and the use of real datasets, and often culminates in a senior capstone or practicum project where teams address a problem posed by a real employer or community partner.

• Core quantitative methods: probability, statistical inference, regression and time-series analysis, optimisation and simulation
• Computing and data management: programming for analytics, database design, data visualisation
• Management and business foundations: managerial accounting, organisational behaviour, operations management, managerial economics
• Applied electives: analytics in finance, supply-chain analytics, risk analysis, marketing metrics
• Experiential learning: internships, research with faculty, senior capstone or practicum

Structure

The degree follows a liberal-arts model, combining general education requirements with major-specific coursework. Small seminar-style classes and project courses are balanced by skill-building labs. Students are encouraged to pursue interdisciplinary minors or certificates (for example computer science, economics or data analytics) and to undertake internships or semester-long off-campus study to broaden practical experience.

Entry requirements

Applicants should present a recognised secondary school completion qualification. Typical academic preparation includes coursework in mathematics (preferably including calculus), and strong performance in quantitative subjects. Recommended supporting materials include transcripts, a personal statement that describes interest in quantitative problem solving and management, and one or more letters of recommendation.

For applicants from qualifications such as A-levels, IB or other national systems, relevant preparation would normally include A-level/IB Higher Level mathematics or equivalent. International applicants submit proof of English proficiency where required. Susquehanna may consider standardised test scores where provided, but admissions decisions are based on the whole application.

Career prospects

Graduates are well placed for roles that require analytical thinking and business knowledge. Common early-career positions include business analyst, data analyst, operations analyst, supply-chain analyst, risk analyst and financial analyst. The combination of quantitative skills and management training also prepares graduates for consulting roles and for further study in fields such as analytics, applied statistics, operations research, business administration or carefully related master’s programmes.

Alumni typically enter the private sector (technology, finance, manufacturing, retail), professional services and consulting firms, or public and non-profit organisations that value data-driven decision making. The programme’s emphasis on internships and capstone projects helps students build portfolios and professional networks that support job placement.

Why study at Susquehanna University

Susquehanna offers this programme within its Sigmund Weis School of Business, combining the benefits of a liberal-arts education with business-focused, experiential learning. Class sizes are small, enabling close faculty mentoring and collaborative project work. Faculty include instructors with both academic and industry experience who supervise applied research and practicum projects.

The university places strong emphasis on hands-on experience: students have access to analytics and computer labs, internships coordinated through the Centre for Career Design, and opportunities to work on client projects with local and regional employers. The campus environment supports interdisciplinary study, study abroad and cross-department minors that allow students to tailor their quantitative and managerial skillset to specific career goals.