St. John's University

What you'll study

This master's focuses on quantitative tools and their application to managerial problems. Core topics typically include statistical inference and applied econometrics, optimisation and linear programming, stochastic models and simulation, forecasting and time series analysis, and decision analysis. Students work with industry-standard software and programming languages such as R, Python, and SQL, and study applications in areas such as supply chain management, revenue management, risk analysis and business analytics.

The programme usually combines coursework with a practical capstone or practicum. Typical modules and subjects are:

• Applied Statistics and Econometrics – regression, model selection, causal inference and forecasting methods.
• Operations Research and Optimisation – linear and integer programming, network flows and production planning.
• Stochastic Processes and Simulation – Markov chains, queuing models and discrete-event simulation for capacity and resource planning.
• Data Analytics and Machine Learning – supervised and unsupervised learning, validation, and deployment for predictive decision-making.
• Database Management and Programming for Analytics – SQL, data cleaning, scripting with Python or R and reproducible workflows.
• Supply Chain and Operations Management – inventory models, logistics, and performance measurement.
• Capstone Project or Practicum – an integrative applied project with a real dataset or an internship with an external partner.

Entry requirements

Applicants are normally expected to hold a recognised bachelor's degree. A quantitative background—such as coursework in calculus, linear algebra, probability, statistics or introductory programming—is preferred. Admissions will consider the whole profile: academic transcripts, a CV, a personal statement outlining relevant experience and goals, and professional or academic references.

Standardised tests (such as the GRE or GMAT) may be optional or recommended depending on the applicant's prior preparation and experience; international applicants are typically required to demonstrate English language proficiency through an approved test unless exempted. Relevant work experience in quantitative or analytical roles can strengthen an application, especially for part-time or executive pathways.

Career prospects

Graduates leave prepared for analytical and decision-focused roles across industry, government and consultancy. Typical job titles include:

• Data Analyst / Data Scientist
• Operations Research Analyst
• Business or Management Analyst
• Supply Chain Analyst / Logistics Planner
• Pricing Analyst / Revenue Manager
• Risk Analyst in finance or insurance
• Analytic Consultant in firms specialising in optimisation and process improvement

The programme also provides preparation for further research or doctoral study in related quantitative fields.

Why study at St. John's University

St. John's University offers access to a metropolitan business environment in New York, with strong links to regional employers and internship opportunities that help students apply quantitative methods to real business problems. The university's business and management faculties emphasise applied teaching and small-group instruction, allowing students to work closely with faculty on projects and research.

Students benefit from university career services, industry events and alumni networks that support recruitment into analytics, operations and consulting roles. The programme's practical orientation—combining statistical rigour, optimisation techniques and hands-on software training—prepares graduates to translate quantitative insight into managerial decisions across sectors.