St. John's University

What you'll study

This programme builds a strong foundation in core mathematical theory while developing computational and modelling skills used in practical applications. The curriculum typically begins with core courses in calculus, linear algebra and differential equations, and progresses to real analysis and probability and statistics.

Upper-level modules focus on applied techniques and numerical methods, including numerical analysis, scientific computing, mathematical modelling, partial differential equations, optimisation and stochastic processes. Students can choose electives that reflect their interests, such as data science and machine learning, financial mathematics, operations research, discrete mathematics, mathematical biology or signal processing.

A hallmark of the degree is hands-on experience: many students complete a capstone project or senior thesis that solves a real problem using mathematical modelling and computation. There are also opportunities for internships with industry partners in the New York area and for using departmental high-performance computing resources and software (for example MATLAB, Python and other scientific libraries).

Entry requirements

Applicants are expected to have a high school diploma or equivalent with a strong background in mathematics. Successful candidates typically present study of algebra, precalculus and calculus; familiarity with calculus at least through differential and integral concepts is important. Physics and programming experience are helpful but not always required.

St. John's considers a range of qualifications from different countries and welcomes students with Advanced Placement, International Baccalaureate or other recognised pre‑university credentials. International applicants must demonstrate English language proficiency where required. Transfer students and mature applicants are considered based on previous tertiary study and relevant experience.

Career prospects

Graduates with a degree in Applied Mathematics have a wide range of career paths available to them. Typical roles include data analyst, data scientist, quantitative analyst in finance, operations research analyst, actuarial trainee, software developer, and roles in engineering and scientific research. The degree also provides strong preparation for graduate study in mathematics, statistics, computer science, engineering and related disciplines.

Because of St. John's location and industry connections, students often obtain internships and entry-level positions with financial firms, technology companies, research centres and government agencies in the New York region and beyond. The programme’s emphasis on computing and modelling helps graduates be workforce-ready in sectors that require numerical methods and data-driven decision making.

Why study at St. John's University

St. John's offers a personalised learning environment within a larger metropolitan university, with access to faculty who combine academic expertise and practical experience. The mathematics and applied mathematics faculty supervise student research projects and maintain connections with local industries, providing internship and collaborative research opportunities.

The university’s location in New York City and its multiple campus sites give students proximity to financial, technology and research organisations, which supports placement and networking. Students benefit from campus computing facilities, dedicated advising and career services that help translate technical skills into professional opportunities. In addition, the university’s mission emphasises ethical leadership and service, which informs how technical education is delivered and applied.