Seattle University

What you'll study

This programme provides a solid foundation in core mathematics while emphasising numerical methods, algorithmic thinking and scientific computing. You will take sequential courses in calculus, multivariable calculus and linear algebra, and move into intermediate topics such as differential equations, probability and statistics, and real analysis. Computational-specific coursework typically includes numerical analysis, scientific computing, numerical linear algebra, mathematical modelling, and algorithm design. Programming and software tools are integrated throughout the curriculum; students commonly learn and apply languages and environments such as Python, MATLAB, or similar platforms in problem sets and labs.

Upper-level work often requires a senior seminar or capstone project in which students apply mathematical and computational methods to a sustained problem, frequently involving data analysis, simulation, or collaboration with faculty on research. Electives allow students to tailor the programme toward interests in data science, applied mathematics, or theoretical mathematics, and may include courses in machine learning, optimization, discrete mathematics, and mathematical statistics.

Entry requirements

Applicants should hold a high-school diploma (or equivalent) with a strong background in mathematics. Recommended preparation includes one or more years of high-school algebra and geometry and exposure to pre-calculus or calculus. Prior experience with calculus is advantageous for placement in first-year university courses. Seattle University evaluates applicants holistically; competitive candidates typically demonstrate consistent academic performance, strong quantitative coursework, and interest in analytical problem solving. International applicants must meet the university’s English proficiency requirements and provide credentials equivalent to U.S. secondary education.

Career prospects

Graduates with a computational mathematics degree are prepared for roles that require quantitative reasoning, programming and numerical modelling. Common career paths include software development, data analysis and data science, quantitative analyst roles in finance, operations research, scientific and engineering computing, and roles in technology companies that require algorithmic and numerical expertise. The degree also provides strong preparation for graduate study in applied mathematics, computer science, statistics or engineering, and for professional certification tracks such as actuarial exams for students who pursue the appropriate statistics and probability coursework.

Why study at Seattle University

Seattle University offers a liberal arts approach within a Jesuit educational tradition, combining rigorous technical training with emphasis on ethical reasoning and communication. Small class sizes and accessible faculty allow for close mentorship, undergraduate research opportunities and collaborative projects. Located in a major technology hub, the university provides proximity to internships and employers in software, aerospace, biotech and other industries, giving students practical experience and networking opportunities. The Department of Mathematics supports student engagement through advising, research seminars and a capstone experience that helps bridge classroom learning with real-world computational challenges.