Fairleigh Dickinson University

What you'll study

This programme combines rigorous quantitative methods with applied management subjects. Core topics typically include statistical inference and applied regression, optimisation (linear and integer programming), stochastic processes and simulation, forecasting and time series analysis, multivariate analysis, and decision analysis. Students also study data management and computing for analytics, with practical training in tools and languages such as Python, R, SQL and spreadsheet optimisation.

The curriculum is usually organised around core modules, a choice of electives, and a culminating experience. Electives enable students to tailor the degree toward interests such as supply chain and logistics analytics, financial risk modelling, healthcare operations, machine learning for business, or advanced econometrics. The programme normally offers a capstone project or practicum that places emphasis on solving a real-world management problem for an external client or on an independent thesis-style research project.

Entry requirements

• A recognised bachelor’s degree in a relevant discipline (for example mathematics, statistics, engineering, economics, computer science, business or a closely related field) or equivalent demonstrated quantitative preparation.
• Academic transcripts showing strong quantitative coursework; applicants without a quantitative undergraduate degree may be required to demonstrate competency through prerequisite coursework in calculus, linear algebra and introductory statistics.
• A personal statement outlining your objectives and how the programme fits your career plans.
• One or two letters of recommendation from academic or professional referees able to comment on your quantitative ability and potential for graduate study.
• For international applicants whose first language is not English, an approved English language qualification is required (for example IELTS or TOEFL) unless otherwise exempt.
• Some applicants may submit GRE or GMAT scores if they wish to strengthen their application, though these are not always mandatory; relevant professional experience in quantitative roles can also be an advantage.

Career prospects

Graduates of this programme are prepared for analytical and decision-focused roles in a wide range of sectors. Typical job titles include data analyst, operations research analyst, management consultant, supply chain analyst, pricing analyst, risk analyst and quantitative modeller. Employers are commonly found in finance, consulting, logistics and transportation, healthcare systems, technology firms and government agencies that require evidence-based decision support.

The skill set developed — statistical modelling, optimisation, simulation, programming and the ability to translate quantitative results into managerial recommendations — also provides a strong foundation for further academic study at the doctoral level or for professional certification in analytics and project management.

Why study at Fairleigh Dickinson University

• Practical, applied focus with opportunities for project-based learning and industry-relevant capstone work that connects students with real organisational problems.
• Faculty with applied research and professional experience in quantitative methods, offering close supervision and mentoring in small‑class settings.
• Flexible study options to accommodate full-time students and working professionals, with a mix of evening, on-campus and online coursework available.
• Strategic location and links to regional employers and networks that support internships, practicum placements and graduate employment opportunities.
• Access to computing resources and software commonly used in industry, preparing students for immediate contribution in analytics and decision‑support roles.