The Bachelor of Science in Applied Mathematics at CUNY is a programme focused on using mathematical theory, computation and modelling to solve real-world problems across science, engineering, finance and data analytics. It suits students with strong quantitative interests who want rigorous mathematical training combined with practical computational and applied skills.
What you'll study
The programme combines core mathematical theory with computational methods and application-focused coursework. Students build a foundation in calculus, linear algebra and differential equations before progressing to more advanced topics and applied electives.
- Core mathematics: single- and multivariable calculus, linear algebra, ordinary differential equations, real analysis or advanced calculus, and proof-writing techniques.
- Applied and computational methods: numerical analysis, scientific computing, numerical linear algebra, computational methods for differential equations, and mathematical modelling.
- Probability and statistics: introductory and intermediate probability, mathematical statistics, stochastic processes and time series analysis.
- Advanced applied topics / electives: partial differential equations, optimisation and operations research, machine learning and data mining, computational finance, actuarial mathematics, and mathematical biology.
- Capstone and practical experience: a senior capstone project or seminar in applied mathematics, opportunities for research with faculty, and practicum or internship options linked to industry partners in New York City.
- Computing and software: coursework and labs emphasise programming and tools commonly used in applied work such as Python, MATLAB, R, and high-performance computing techniques.
Entry requirements
Applicants normally require a high school diploma or equivalent with strong preparation in mathematics. Recommended background includes calculus (or multivariable calculus for stronger applicants), algebra, and familiarity with precalculus concepts; coursework in physics or computer science is advantageous.
- Successful applicants typically demonstrate strong performance in mathematics subjects and provide transcripts that reflect sustained quantitative achievement.
- Standardised test scores (where used) and placement testing may inform course placement, but policies vary by campus and applicant category.
- Transfer applicants must submit college transcripts; prior calculus and linear algebra should be documented. Mature students and those with relevant work experience are considered through the university's standard admissions procedures.
- International applicants should meet general CUNY admission criteria for international students, including proof of secondary education and English language proficiency where required.
Career prospects
Graduates of an Applied Mathematics degree have a wide range of career options across private and public sectors due to their ability to model complex systems and work with data and algorithms.
- Data science and analytics: roles in data analysis, machine learning, and business intelligence across technology, media and healthcare sectors.
- Finance and quantitative roles: quantitative analyst, risk analyst, or roles in algorithmic trading and financial modelling; some paths require professional actuarial or finance exams.
- Engineering and technology: computational modelling, software development, simulation and systems design.
- Operations research and optimisation: supply chain analysis, logistics, and decision-support roles in industry and government.
- Research and academia: graduate study (MSc/PhD) in applied mathematics, statistics, computational science or interdisciplinary fields.
- Public sector and consulting: policy analysis, environmental modelling, epidemiology modelling, and technical consulting.
Why study at CUNY(The City University of New York)
CUNY offers access to the resources of a public urban university system with strong connections to New York City's industry and research communities. Students benefit from faculty who work on applied problems, opportunities for internships with financial firms, tech companies and public agencies, and research collaborations across campuses.
- Urban location provides extensive internship and employment networks in finance, technology, media and government.
- Diverse student body and supportive services that help students from a wide range of backgrounds succeed in quantitative fields.
- Opportunities to collaborate with departments across the university system—such as computer science, engineering, economics and public health—for interdisciplinary training.
- Practical training in contemporary computing tools and access to computing facilities and research centres that support applied and computational projects.
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