Focus On Majors: Applied Mathematics
Applied mathematics is the study of mathematical methods and how they're used to address problems in science, engineering, business, and other fields. It sits between pure mathematics and the applied disciplines that use math as a tool. Students build skills in calculus, linear algebra, differential equations, probability, and computational methods, then learn to apply those to real-world problems.
Most programs encourage students to develop depth in a second subject. This gives the degree a lot of range, which is one reason it can appeal to students with strong quantitative skills who haven't yet settled on a specific direction.
Students who do well in applied mathematics tend to arrive with a solid math foundation. The most useful courses are calculus and statistics. Physics is worth prioritizing, since it's often used to describe real systems. A computer science class or programming skills can also prepare a student for the major.
In terms of mindset, students who tend to do well in applied mathematics are comfortable sitting with a problem that doesn't have an obvious answer. They're generally more interested in understanding WHY a method works than in simply getting the right answer. A natural curiosity about how things are measured, predicted, or modeled is an initial indicator of a possible good fit.
For applied math specifically, a flexible curriculum may matter more than it might for other majors because the degree's real value comes from pairing math with another field. Schools that don't require a specific list of general education (GE) courses or narrow GE categories give students more room to explore “applying” mathematics.
Brown's Open Curriculum allows applied mathematics majors at Brown to spend elective credits learning a second field. Their applied mathematics concentration offers tracks in biology, computer science, economics, and physics, and students can pursue independent research through the Division of Applied Mathematics, which spans fluid dynamics, mathematical biology, and machine learning theory.
With the "Rochester Curriculum," instead of fixed core requirements, students choose three clusters of study: one in their major and two others built around their own interests. It's a similar philosophy to Brown's but at a more accessible admissions level. Applied math majors here can double major in economics, computer science, or other fields without the friction of narrow GE requirements.
USC offers a five-year combined Bachelor's and Master's in Applied Mathematics. Students apply during their sophomore or junior year and take graduate-level courses that count toward both degrees simultaneously. The 4+1 structure is worth considering for students who know they want to go further in the field. The minor a student chooses often clarifies where their skills will be applied.
Common pairings:
Computer Science - Moves students toward software, machine learning, or AI roles
Economics - Useful for quantitative finance, policy analysis, or consulting
Biology or Neuroscience - Connects to computational biology, bioinformatics, or research
Statistics - Deepens the credentials for data science or research tracks
Public Health - Relevant for health policy and global health organizations
Psychology / Cognitive Science - A path into User Experience (UX) research, behavioral economics, and human-computer interaction
For students interested in building AI systems, machine learning runs on linear algebra, calculus, and probability. As AI tools become more common across industries, knowing what a model's output actually means and when to question it requires the same analytical thinking learned in applied mathematics curricula. The ability to interpret a result is increasingly useful.
Career Paths for Applied Mathematics Majors
Actuary
Biostatistician
Climate/Environmental Modeler
Computational Biologist
Cryptographer/Cybersecurity Analyst
Data Scientist
Econometrician
Epidemiologist
Financial/Quantitative Analyst
Machine Learning Engineer
Operations Research Analyst
Quantitative Risk Manager
Research Scientist
Signal Processing Engineer
Software Engineer
Supply Chain Analyst
University Researcher/Professor
UX Researcher (Quantitative)
