University of San Diego

What you'll study

This programme develops mathematical, statistical and computational skills used to model and solve complex managerial problems. Teaching balances theory and practical application through core modules, electives and a culminating project. Typical areas of study include:

• Quantitative Foundations: probability and mathematical statistics, regression and time-series analysis, econometrics.
• Operations Research and Optimisation: linear and nonlinear programming, stochastic models, simulation, network flows.
• Data Analytics and Computing: data management and SQL, machine learning and predictive analytics, programming for analytics (commonly Python or R).
• Decision Analysis and Risk: decision theory, Bayesian methods, risk assessment and scenario analysis.
• Applications and Electives: supply chain analytics, finance analytics, healthcare operations, marketing analytics, and policy modelling.
• Capstone or Practicum: an industry-sponsored project or applied research dissertation that integrates quantitative methods to address a real organisational problem.

Delivery typically combines lectures, case studies, lab sessions with statistical and optimisation software, and team-based projects. Students gain hands-on experience with data cleaning, model building, interpretation of results and communicating quantitative insights to non-technical stakeholders.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree from an accredited institution. Typical entry expectations include:

• A strong undergraduate background in a quantitative discipline (for example mathematics, statistics, engineering, economics, computer science or a business degree with substantial quantitative coursework).
• Evidence of mathematical and statistical competence — prior coursework in calculus and introductory statistics is usually required; additional preparation in linear algebra and probability is advantageous.
• Academic transcripts and a résumé or CV outlining relevant academic or professional experience.
• One or more letters of recommendation and a personal statement describing academic interests and career goals.
• Standardised test scores (GMAT or GRE) may be requested or considered in the admissions process, depending on the applicant’s profile; professional experience can sometimes substitute for formal test scores.
• For international applicants, proof of English language proficiency via recognised tests unless exempted by prior education in English.

Applicants with limited programming or statistical software experience may be advised to complete preparatory coursework or online modules before entry.

Career prospects

Graduates leave with a toolkit that is highly sought after across sectors. Common career paths include:

• Data analyst, business analyst or data scientist roles using statistical modelling and machine learning to inform decisions.
• Operations research or optimisation analyst positions in manufacturing, logistics and supply chain management.
• Quantitative analyst roles in finance and risk management, including forecasting and portfolio analysis.
• Consultancy positions that provide analytics-driven recommendations to corporate or public sector clients.
• Analytic roles in healthcare systems, utilities and government agencies focused on resource allocation, scheduling and policy evaluation.

Graduates also progress to managerial analytics positions or continue to doctoral research in areas such as operations research, applied statistics or management science.

Why study at University of San Diego

The University of San Diego offers this programme within a business-focused environment that emphasises experiential learning and ethical leadership. Students benefit from small class sizes, close faculty mentorship and access to computing labs and analytics software. The university’s location provides strong links to San Diego’s diverse industry base — including biotech, defence, logistics and technology — creating opportunities for internships, practicum projects and employer engagement.

USD’s institutional values emphasise ethical decision-making and social responsibility, which are woven into coursework and projects to prepare graduates to apply quantitative methods responsibly. Career services and an active alumni network support professional development and job placement after graduation.