Lesley University

What you'll study

The curriculum emphasises both theoretical foundations and practical applications. You will take core courses in calculus, linear algebra, differential equations and probability and statistics, alongside applied modules that introduce mathematical modelling, numerical analysis, computational methods and data science techniques. Typical topics and modules include:

• Calculus sequence — single-variable and multivariable calculus with applications.
• Linear Algebra — matrix theory, vector spaces, and applications to systems and modelling.
• Differential Equations — ordinary and partial differential equations used to model dynamic systems.
• Probability and Statistics — foundations of inference, regression, and stochastic processes.
• Numerical Analysis and Scientific Computing — numerical methods for solving mathematical problems and implementation using common scientific computing tools.
• Mathematical Modelling — translating real-world situations into mathematical form and validating models against data.
• Data Analysis and Machine Learning — applied data-processing techniques, exploratory data analysis and introduction to machine-learning methods.
• Capstone or Senior Project — a supervised, open-ended project emphasising modelling, computation and communication of results.

Electives will allow you to tailor the degree toward areas such as actuarial science, computational mathematics, operations research, economics or interdisciplinary projects with the sciences. Hands-on elements typically include programming assignments, laboratory-style computing sessions, group projects and opportunities for undergraduate research with faculty.

Entry requirements

Applicants are normally expected to hold a recognised secondary school diploma or equivalent. Strong preparation in mathematics is required—evidence of coursework such as higher-level algebra, precalculus or calculus is typically expected. Lesley Admissions will consider the full application package: academic transcripts, personal statement, letters of recommendation and any relevant extracurricular experience or portfolio materials.

Because Lesley emphasises personalised learning, applicants with non-traditional backgrounds who can demonstrate quantitative ability through prior study, work experience or portfolio work are also encouraged to apply. Standardised tests may be optional or considered as part of a broader review depending on the applicant’s circumstances; consult Lesley’s admissions guidance for current policies.

Career prospects

Graduates with a degree in applied mathematics have a wide range of career options. Typical roles include:

• Data analyst, data scientist or business intelligence analyst
• Quantitative analyst or financial modeller in banking and finance
• Actuarial trainee (with further professional exams)
• Operations research analyst or optimisation specialist
• Software developer or computational scientist working on numerical methods
• Research assistant or laboratory analyst in science and engineering settings
• Secondary school mathematics teacher (with appropriate certification)

Many alumni also pursue graduate study in applied mathematics, statistics, engineering, computer science, economics or related professional programmes. The programme’s emphasis on modelling, computation and communication equips graduates to move into industry roles or continue to postgraduate research.

Why study at Lesley University

Lesley University offers a liberal-arts environment with small class sizes and close faculty mentorship, which supports in-depth learning and personalised advising. The university’s location in the Boston–Cambridge area gives access to local research institutions, technology companies and internship opportunities that complement applied mathematics training.

Students benefit from experiential learning approaches: collaborative projects, undergraduate research opportunities, and connections across disciplines such as the sciences, education and the arts. Faculty typically include instructors active in teaching-focused scholarship and applied research, helping students develop both conceptual understanding and practical skills valued by employers and graduate programmes.