undergradly.
Major · Multi/Interdisciplinary

Where mathematical rigor meets software and data work

Mathematics and Computer Science (CIP 30.0801) is the interdisciplinary bachelor’s synthesizing math and CS coursework. About 1,125 students complete it across 78 institutions; bachelor’s grads earn $120,604 — among the highest 5-year medians in the IPEDS data — driven by hiring into software development, data science, and quantitative finance.

Schools offering
78
Annual completions
1,125
Typical degree level
Associate's + Bachelor's
Median earnings (5yr)
$121k

About this major

Mathematics and Computer Science (CIP 30.0801) is the interdisciplinary bachelor’s synthesizing math and CS coursework into a single rigorous degree. The CIP definition reads as a general synthesis of mathematics and computer science or a specialization drawing from both. Coursework typically combines a computer-science core — algorithms, data structures, systems, theory of computation, programming languages — with a math core — calculus, linear algebra, discrete mathematics, real analysis, abstract algebra, probability and statistics — plus advanced electives in machine learning, cryptography, numerical methods, or operations research. Programs vary in balance: Harvey Mudd’s leans research-heavy, UC schools blend industry preparation with theory, and UIUC’s tracks toward systems and computation theory.

The major fits students who want stronger theoretical foundations than a pure CS major delivers — typically because they’re aiming at machine learning, quantitative finance, cryptography, scientific computing, or graduate study. It rewards persistence on hard problems, comfort with formal proof writing, and mathematical maturity rather than raw coding speed. Day-to-day at the undergraduate level mixes problem sets that take hours to crack, programming projects that combine algorithmic depth with implementation discipline, and the kind of upper-division coursework where one course (real analysis, theory of computation) becomes the semester.

One grounded observation about scale and labor-market positioning: 1,125 students complete this CIP across just 78 institutions, with bachelor’s grads earning $120,604 — among the highest 5-year medians in the IPEDS data. The wage reflects three converging factors: top-quartile-prepared students at academically rigorous institutions (UC San Diego alone produces 338 completions, about 30% of the national total, with Santa Clara, UIUC, Harvey Mudd, and UC Irvine rounding out the list), destinations in software, data, and quant roles paying at tech-industry rates, and the labor market’s premium for ML and AI specializations. The packet’s tracked occupations include Software developers ($133,080, 15.8% growth), Computer and information systems managers ($171,200, 15.2% growth), and Data scientists ($112,590, 33.5% growth) — all bachelor’s-coded — with research-track destinations gated behind doctoral degrees in CS, applied math, statistics, or operations research.

Section 3 · Careers

Where this major leads

Occupations most often associated with this major, from the federal BLS+O*NET crosswalk. Job-growth projections and median wages are national.

Occupation Median wage Job growth Typical education
Software developers $133k +15.8% Bachelor's degree
Computer and information systems managers $171k +15.2% Bachelor's degree
Computer occupations, all other $109k +8.2% Bachelor's degree
Data scientists $113k +33.5% Bachelor's degree
Natural sciences managers $161k +3.7% Bachelor's degree
Mathematical science teachers, postsecondary $79k +2.3% Doctoral or professional degree
Computer science teachers, postsecondary $97k +5.3% Doctoral or professional degree
Mathematical science occupations, all other $71k +4.0% Bachelor's degree
Section 4 · Earnings

Earnings at a glance

Median graduate earnings from the federal College Scorecard, 5 and 10 years out.

Median 5-year earnings

$121k

Who this major is for

Good signs this major fits: you have strong calculus and proof-writing foundations from high school or first-year college coursework and enjoy spending hours on a single hard problem; you’re aiming at machine learning, quantitative finance, cryptography, scientific computing, or graduate study and want a credential that signals theoretical depth; you’re drawn to the kind of upper-division courses (real analysis, theory of computation, abstract algebra) where one class becomes a semester; you want flexibility to ladder into a CS, applied-math, statistics, or operations-research graduate program later; and the strong $120,604 bachelor’s median in the data fits your career calculus.

Reasons to pause: the major rewards mathematical maturity over raw coding speed, and students who struggled with calculus II, discrete mathematics, or linear algebra in their first year often lose ground that compounds in upper-division courses. If your primary goal is building software for industry without the research-track ramp, the standard Computer Science major (CIP 11.0701, 50,272 completions) is less mathematically demanding and equally well-paid for typical software-engineering destinations. The wage data is heavily skewed by top-feeder schools (UCSD, Harvey Mudd, UIUC, Santa Clara) — verify the specific program’s placement outcomes and graduate-school feeder rates before assuming the headline number applies. Recent tech-industry layoffs have compressed entry-level CS hiring; the labor market still pays top-quartile graduates well but is less forgiving than in 2020-2022.

Section 6 · Where to study

Top colleges for Mathematics and Computer Science

Ranked by annual completions at the associate's or bachelor's level — a proxy for program scale.

College Location Assoc. Bach. Total
University of California-San Diego La Jolla, CA 0 338 338
Santa Clara University Santa Clara, CA 0 90 90
University of Illinois Urbana-Champaign Champaign, IL 0 83 83
George Mason University Fairfax, VA 0 65 65
Harvey Mudd College Claremont, CA 0 52 52
University of California-Irvine Irvine, CA 0 48 48
Washington University in St Louis St. Louis, MO 0 46 46
University of Illinois Chicago Chicago, IL 0 45 45
Minerva University San Francisco, CA 0 43 43
University of Akron Main Campus Akron, OH 0 35 35
Section 7 · Explore sideways

Related majors to explore

Computer Science

50,272 completions/yr

Computer and Information Sciences, General

34,556 completions/yr

Information Technology

20,296 completions/yr

Mathematics, General

18,758 completions/yr

Information Science/Studies

10,334 completions/yr

Management Information Systems, General

7,648 completions/yr

Computer Programming/Programmer, General

5,205 completions/yr

Computer Systems Networking and Telecommunications

3,699 completions/yr
Section 9 · Frequently asked

Common questions

What does this major actually involve?
The CIP definition centers on a synthesis of mathematics and computer science. Coursework typically combines a computer science core (algorithms, data structures, systems, theory of computation, programming languages) with a math core (calculus, linear algebra, discrete mathematics, real analysis, abstract algebra, probability and statistics) plus electives in machine learning, cryptography, numerical methods, or operations research. Programs vary in balance — some lean closer to applied math, others closer to theoretical CS.
Is this just Computer Science with extra math?
Effectively, yes — and that’s the point. Students who pick this CIP usually want stronger theoretical foundations than a pure CS major delivers, often because they’re aiming at machine learning, quantitative finance, cryptography, scientific computing, graduate study, or competitive programming and research-track work. The labor market generally values it equivalently to Computer Science (CIP 11.0701, 50,272 completions) for software roles, with a slight premium for ML, quant, and research-heavy positions.
What jobs do graduates land?
The packet names eight occupations, with the strongest being Software developers ($133,080, 15.8% growth), Computer and information systems managers ($171,200, 15.2% growth), Data scientists ($112,590, 33.5% growth), and Computer occupations all other ($108,970, 8.2% growth). Realistic entry destinations include software engineering at large tech companies (Google, Meta, Amazon, Microsoft), quantitative analyst roles in finance, machine-learning engineering, data science, scientific computing at national labs, and graduate study in CS, math, or applied mathematics.
Why is the wage so much higher than other multi-interdisciplinary CIPs?
The packet’s $120,604 5-year median reflects three factors. First, the major attracts top-quartile-prepared students at academically rigorous institutions — UC San Diego alone produces 338 completions (30% of the national total), with Santa Clara, UIUC, Harvey Mudd, and UC Irvine rounding out the list. Second, the destinations are software, data, and quant roles paying at tech-industry rates, not generic math-or-CS-adjacent positions. Third, the CS labor market in 2024-2025 commands premium wages despite recent layoffs, particularly for ML and AI specializations.
How do I know if I’m strong enough for this major?
Strong calculus and proof-writing performance in high school or first-year college coursework is the realistic gate. Students who struggle with calculus II, discrete mathematics, or linear algebra in their first year often lose ground that compounds in upper-division real analysis, theory of computation, and algorithms. The major rewards persistence on hard problems more than raw speed; if you enjoy spending hours on a single proof or a single difficult algorithm, this is the right fit. If you primarily want to build software, the standard CS major (11.0701) is less mathematically demanding and equally well-paid for industry work.
What’s the typical next step?
Three common paths: direct industry entry into software engineering, ML engineering, or quantitative analyst roles (most graduates); graduate study in computer science, applied mathematics, statistics, or operations research (a meaningful minority — particularly from Harvey Mudd, UIUC, and UC schools); or quantitative finance via PhD or master’s in financial engineering (smaller but well-paid stream). The bachelor’s alone is enough for industry; graduate study is the path for research, academia, or the highest-paying quant and ML-research roles.