St. John's University

What you'll study

This programme blends core business subjects with quantitative and computational methods to prepare students to analyse complex organisational problems. You will take foundational courses in microeconomics, managerial accounting, corporate finance and organisational behaviour alongside a sequence of quantitative modules.

• Mathematics and statistics: calculus, linear algebra, probability and mathematical statistics that underpin modelling and inference.
• Quantitative methods: operations research and optimisation, simulation, decision analysis, forecasting and time-series analysis.
• Data and computing: database fundamentals, data management, programming for analytics (commonly using languages such as Python, R or similar), and data visualisation.
• Business analytics and econometrics: applied regression, causal inference, machine learning for managerial contexts and econometric techniques for business data.
• Functional business knowledge: courses in marketing, supply chain management, information systems and corporate finance to provide context for quantitative work.
• Capstone and experiential learning: a senior project or practicum that applies quantitative methods to a real-world business problem, plus opportunities for internships and industry-linked projects.

Students typically follow a structured curriculum with prerequisites that build from introductory mathematics and statistics to advanced analytics and optimisation. Electives allow specialisation toward interests such as supply chain analytics, financial engineering or business intelligence.

Entry requirements

Applicants are expected to hold an appropriate secondary school qualification or equivalent. Successful candidates typically demonstrate strong performance in mathematics and quantitative subjects at secondary level and provide evidence of analytic aptitude.

• Academic background: solid preparation in high-school mathematics (algebra, pre-calculus or calculus where available); courses in economics or statistics are advantageous.
• Documentation: official transcripts and any required supporting documents from your secondary education provider.
• English language: for applicants whose first language is not English, proof of English proficiency is required (accepted tests or recognised qualifications fulfil this requirement).
• Additional factors: personal statement, references, and any relevant extracurricular experience (such as maths clubs, coding projects, internships) are considered in the selection process.

Specific admission criteria and processes (including any standardised-test policies or portfolio requirements) are published by the university and may be reviewed as part of the application.

Career prospects

Graduates are well placed for roles that demand quantitative rigour and business understanding. Common career destinations include:

• business/data analyst, applying statistical methods and dashboards to inform management decisions;
• operations or supply chain analyst, using optimisation and simulation to improve processes;
• financial analyst or risk analyst in banking, insurance or corporate finance;
• management consultant specialising in analytics-driven strategy;
• roles in technology firms focused on product analytics, pricing or customer insights.

Alumni also progress to postgraduate study in fields such as business analytics, finance, operations research or MBA programmes, and some pursue research degrees if they are interested in academic or advanced technical careers.

Why study at St. John's University

St. John's offers this programme through a business faculty with a focus on applied learning and industry engagement. The university's location provides access to a wide range of internship and employer partnerships, enabling students to apply quantitative methods to real organisational challenges.

• Applied focus: emphasis on hands-on projects, capstones and practicum placements that build workplace-ready skills.
• Faculty expertise: instructors with academic and industry experience in analytics, operations research and business disciplines.
• Facilities and resources: access to computing labs, data tools and career services that support recruitment into analytics, finance and consulting roles.
• Alumni and industry links: professional networks and employer relationships that help with internships and graduate employment.

The programme is designed to produce graduates who can translate quantitative analysis into actionable business insight, making them valuable to employers across sectors that rely on data-driven decision making.