Cost & earnings at Pfeiffer University What students borrow here, and what they go on to earn
The Bachelor of Science in Mathematics with a concentration in Computational Mathematics at Pfeiffer University combines rigorous mathematical theory with practical computing skills to model and solve real-world problems. It suits students who enjoy abstract reasoning and algorithmic thinking and who want preparation for technical careers or further study in applied mathematics, data science or engineering-related fields.
The Computational Mathematics programme builds a solid foundation in pure and applied mathematics while emphasising numerical methods and computer-based problem solving. Core topics include calculus, linear algebra, multivariable calculus, ordinary differential equations and probability and statistics. From the applied side you will encounter numerical analysis, scientific computing, mathematical modelling, optimization and partial differential equations. Courses in discrete mathematics, algorithms and computational complexity provide the theoretical underpinning for algorithm design.
Practical computing skills are woven throughout the curriculum. Typical programming and software topics include structured and object-oriented programming, data structures, numerical libraries, MATLAB or Python for scientific computing, and use of statistical computing tools. Students complete a senior capstone or research project that applies mathematical techniques and software to a modelling or data analysis problem. General education requirements ensure breadth across the liberal arts, and elective options allow you to tailor the degree toward areas such as data science, actuarial science, finance or engineering.
Applicants should hold a high school diploma or equivalent with a strong background in mathematics. Preparatory coursework in algebra, geometry, trigonometry and, ideally, high school calculus is expected. Pfeiffer evaluates applicants holistically; typical admits demonstrate consistent academic performance, teacher recommendations and engagement in quantitative or analytical activities (for example, math club, competitions, coding projects or internships).
Transfer applicants should present college-level transcripts showing success in foundational mathematics courses. International applicants must meet Pfeiffer's standard English-language proficiency and credential evaluation requirements. Because this is a mathematically intensive programme, students who are uncertain about preparedness are encouraged to contact the department for placement guidance or to take preparatory courses.
Graduates with a computational mathematics degree are well positioned for roles that require quantitative reasoning and programming skills. Common entry-level career paths include data analyst, quantitative analyst, software developer, operations research analyst, actuarial analyst and technical consultant. The programme also prepares students for graduate study in applied mathematics, statistics, computer science, data science, engineering or business analytics.
Because the curriculum emphasises numerical modelling and computational implementation, alumni work in sectors such as finance, technology, healthcare analytics, manufacturing, government and research institutions. The capstone and internship components help students build portfolios of applied projects and industry contacts that support job searches or applications to postgraduate programmes.
Pfeiffer offers a personalised learning environment with small class sizes and close faculty mentoring, which benefits students tackling mathematically challenging and project-based coursework. The mathematics faculty are accessible for independent study and research supervision, and students regularly bring applied problems into class projects and capstone work.
The programme balances theoretical rigour with hands-on computing experience using contemporary tools and languages common in industry and research. Pfeiffer's liberal arts setting encourages interdisciplinary collaboration, making it straightforward to combine mathematics with computer science, economics or natural sciences. Local internship opportunities and the university's alumni network support professional development and experiential learning in regional employers and graduate programmes.
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