Widener University

What you'll study

The programme combines core quantitative methods, applied analytics and decision-support techniques. Typical modules cover statistical inference and regression, multivariate analysis, optimisation and linear programming, stochastic processes and simulation, forecasting methods, and advanced data analytics (including machine learning and predictive modelling). Students also study database management and data visualisation, programming for analytics (commonly using Python or R), and decision analysis for management.

Instruction emphasises application: courses include hands-on problem sets, case studies drawn from operations, finance and healthcare, and software labs. Many students complete a capstone project or practicum with a real organisational sponsor, synthesising modelling, data handling and presentation of results; elective options allow deeper study in areas such as supply chain analytics, risk modelling, or business intelligence.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree or equivalent. A background in quantitative subjects (for example mathematics, statistics, engineering, economics, computer science or a quantitatively oriented business degree) is preferred; applicants without a strong quantitative background may be asked to complete preparatory coursework.

Typical application materials include academic transcripts, a current CV or résumé, a personal statement outlining objectives and preparation for advanced quantitative study, and one or more academic or professional references. Standardised tests (such as the GRE) may be requested in some cases at the university’s discretion. International applicants must demonstrate English proficiency through accepted tests or prior study in English unless exempt.

Career prospects

Graduates are prepared for roles that rely on quantitative analysis and data-driven decision making. Common job titles include data analyst, business analyst, operations research analyst, supply chain analyst, pricing analyst, risk analyst and analytics consultant. Employers span industries such as finance, healthcare, manufacturing, logistics, consulting and the public sector.

The programme equips students with practical skills valued by employers: statistical modelling, optimisation, simulation, programming for analytics, data management and clear communication of technical results to managers and stakeholders. Many alumni move into analytics teams, optimisation and planning groups, or pursue further study at the doctoral level or professional certifications in analytics or project management.

Why study at Widener University

Widener offers a focused, applied approach to management science within a mid-sized university environment that features small class sizes and accessible faculty. The programme leverages practical learning through capstones, practicum placements and industry partnerships, enabling students to work on real problems and build professional networks.

The university’s location provides proximity to regional business hubs and a variety of employers, supporting internship and employment opportunities. Students also benefit from career services, workshops and alumni connections that help translate technical skills into successful careers.