What Can You Do With a Math Degree? Careers, Salaries, and How to Get Hired

TL;DR: Your math degree qualifies you for some of the fastest-growing, best-paying careers in the country. Employers in data science, finance, actuarial work, tech, and operations research all need people who can model problems, quantify risk, and spot patterns in messy data. The BLS projects 21% growth for math occupations through 2034, which is roughly four times the national average.

• Median salaries for math careers range from $70K (data analyst) to $160K+ (quantitative analyst), and most paths have strong upward mobility.

• This guide breaks down 12+ specific job titles with salary data, growth rates, and what the work actually looks like day-to-day.

• You don't need a master's degree or prior experience to start. Externships, portfolio projects, and the right resume framing can get you interviews.

• Pick one career path below, then jump to "How to Get Hired" for your first concrete step.

Not sure how to get real quantitative experience before graduation? Externships are structured 8-week programs where you complete real projects for real companies, from data analytics to financial modeling. Explore Externships →

What Can You Actually Do With a Math Degree?

Way more than most people expect. And that's not optimism talking. It's the hiring data.

If you're studying math (or thinking about it), you're part of a broader liberal arts tradition built on analytical reasoning, structured problem-solving, and adaptability. But math majors have a specific edge that other liberal arts grads don't: the quantitative skills you pick up are in high demand across basically every industry right now.

Why Employers Want Math Majors Right Now

Here's the short version. According to the Bureau of Labor Statistics, math occupations are projected to grow 21% from 2024 to 2034. That's roughly four times the average for all occupations. The median annual wage? $104,860. For context, the national median across all jobs is $48,060.

So why the surge in demand? Companies in finance, tech, healthcare, and government all need people who can build models, interpret data, and make predictions when the data is incomplete or noisy. And no, AI hasn't replaced that need. If anything, it's made it bigger. Every new algorithm still requires someone who actually understands the math underneath it.

Pure Math vs Applied Math: Does Your Track Matter?

This is probably the most common anxiety math students bring up. The honest answer: it matters less than you think.

Applied math programs tend to include more programming, statistics, and domain-specific modeling (differential equations for engineering, stochastic processes for finance). So applied math grads do have a slightly more direct on-ramp into industry roles. But pure math graduates still qualify for the vast majority of careers on this list. Employers care way more about your ability to learn new tools quickly than whether your transcript reads "Abstract Algebra" or "Numerical Methods."

The one real exception? Software engineering and machine learning engineering, where demonstrated coding ability trumps proof-writing skill. If you're a pure math major eyeing those paths, supplement with Python and SQL through coursework or self-study.

What Skills Do Math Majors Bring to the Job Market?

The gap between "what you study" and "what employers want" is smaller than you'd guess. Math coursework builds three skill categories that translate directly into high-paying roles. Want to see how to actually put these on a resume? Check out our guide to skills that matter to employers in 2026.

Quantitative Analysis and Statistical Modeling

Linear algebra, probability theory, real analysis. They sound academic because they are. But on a job description, those same skills show up as "data modeling," "risk quantification," and "statistical forecasting." LinkedIn's 2025 Most In-Demand Skills report ranks data analysis and statistical analysis in the top 10 skills employers search for globally. You've been building those skills every semester.

Logical Problem-Solving and Algorithmic Thinking

Writing proofs teaches you to break messy problems into smaller, provable steps. That's the same skill software engineers use for debugging, consultants use for case interviews, and operations analysts use for process optimization.

Here's a concrete example. When a McKinsey case interview asks you to structure a market-entry analysis, you're essentially constructing a mathematical proof: define your assumptions, build logical steps, test your conclusion. Most business majors have to learn that framework from scratch. You've been practicing it since sophomore year.

Technical Literacy (Python, R, SQL, MATLAB)

Most modern math programs now require some computational coursework. If you've touched MATLAB for numerical methods, R for statistical analysis, or Python for any class project, you already have technical skills that separate you from other non-STEM graduates. Even basic proficiency opens doors. Seriously. SQL alone qualifies you for a surprising number of data analyst roles.

What Are the Best Jobs for Math Majors in 2026?

Below are 12 careers where a math background gives you a real competitive advantage. Each includes median salary data from the BLS and projected growth rates.

One thing before we dive in: salary figures are medians, which means half of workers earn more and half earn less. Your actual starting salary depends on location, company size, and how well you position your skills. But these numbers give you a reliable baseline for comparison.

Data Scientist

This is the role everyone's heard of, and for good reason. Data scientists build models that drive company decisions, everything from which products to launch to how much inventory to stock. Day-to-day, you'll clean datasets, run A/B tests, build machine learning pipelines, and translate findings for product or business teams.

The BLS pegs the median salary at $112,590, with 36% projected growth through 2033. That growth number is staggering. A math degree covers the statistical theory the role demands. Pair it with Python and SQL proficiency, and you're a legitimate candidate at tech companies, healthcare organizations, and consulting firms straight out of undergrad. If you want to build real data analysis experience before applying, the Breaking Games E-Commerce Data Analysis Strategy Externship lets you work with real e-commerce datasets and build the kind of portfolio project that hiring managers actually look for.

Actuary

The classic math career, and it's classic for a reason: actuaries earn well, have strong job security, and follow a clear, structured career ladder. You'll use probability, statistics, and financial theory to assess risk for insurance companies, pension funds, and consulting firms.

Median salary: $125,770. Projected growth: 24%.

The catch is the exam pathway. You'll need to pass a series of professional exams administered by the SOA or CAS, and most candidates start studying for Exam P/1 while still in school. It's a grind. But if you like the idea of a career where your math skills are the core product (not just a nice-to-have), actuarial science is hard to beat.

Statistician

Statisticians are the methodologists behind the data. They design surveys, develop analytical frameworks, and build the inferential tools that other analysts rely on. Think of it as the more rigorous sibling of data science, with heavier emphasis on experimental design and statistical theory.

Median salary: $104,110. Growth: 30%. Pharmaceutical companies (clinical trial design), government agencies (census and economic data), and tech companies (experimentation platforms) are all hiring aggressively for this role.

Financial Analyst

Financial analysts evaluate investments, build valuation models, and advise companies on where to allocate capital. What's interesting for math majors is that the modeling depth from your coursework often exceeds what finance and accounting programs teach. You're not behind your peers in this field. You might actually be ahead.

Median salary sits at $99,890, with 8% growth. If finance sounds appealing, our economics degree jobs guide covers related paths where math and econ skills overlap. You can also get hands-on financial modeling experience through the Energy Innovation Capital Venture Capital Deal Sourcing Externship, where you'll evaluate startups and build real valuation models with professional mentorship.

Quantitative Analyst

This is the highest-ceiling role on the list. Quants build pricing models, develop trading algorithms, and manage risk for hedge funds, investment banks, and prop trading firms. Entry-level compensation at top firms starts around $150K to $200K (base plus bonus), according to data from Levels.fyi and Glassdoor.

The tradeoff? Most quant positions expect a master's or PhD. But some firms do hire exceptional undergraduates for junior roles or rotational programs. If you're pulling top grades in probability, stochastic processes, and numerical methods, it's worth applying. The worst they can say is no.

Operations Research Analyst

Honestly, this might be the most underrated career on the entire list. Operations research analysts use mathematical models to solve logistics problems: optimizing supply chains, scheduling airline routes, allocating military resources, improving hospital patient flow.

Median salary: $83,640. Growth: 23%. If you genuinely enjoyed optimization or linear programming in your coursework (and I mean enjoyed, not just survived), this path is a natural fit. The work is deeply mathematical, and the problems are tangible in a way that pure research sometimes isn't. Want a taste of what this looks like in practice? The Amazon Fulfillment Center Operational Strategy Externship has you working on real supply chain optimization and people analytics problems for one of the largest logistics operations in the world.

Data Analyst

If you want to work with data but aren't sure where to start, this is your entry point. Data analysts use SQL, Excel, and visualization tools like Tableau or Power BI to pull insights from business data and present findings to stakeholders. The median salary is around $70,000, according to Glassdoor and BLS estimates.

Here's what makes this role strategic: many data analysts move into data science or analytics engineering within two to three years. It's a launchpad, not a dead end. If this path appeals to you, our data analyst internship guide walks you through building the right portfolio and landing your first role. You can also build data visualization and analysis skills through the Canva Data Visualization AI Design Externship, which is a great way to add a brand-name project to your portfolio.

Software Engineer / Developer

Math graduates who code are genuinely competitive for software engineering roles, especially at companies where algorithm design, optimization, and performance matter. Think search engines, fintech platforms, game studios.

The BLS median for software developers is $132,270. You won't compete for generic web development positions with a math degree alone, but roles involving computational geometry, algorithm optimization, or backend systems really do value your mathematical background. The key is proving you can ship code, not just write proofs.

Machine Learning Engineer

ML engineers build and deploy the models that data scientists prototype. Linear algebra, calculus, and statistics aren't nice-to-haves for this role. They're prerequisites.

Salaries range from $120K to $180K depending on experience and location, according to Indeed and Glassdoor. Growth tracks alongside data science at roughly 36%. If you've taken courses in optimization, probability, and numerical methods, you genuinely have a head start over CS majors who skipped the theory. That said, you'll need strong programming skills too. Python is non-negotiable. If you want to get hands-on with AI and data extraction before applying, the Outamation AI-Powered Document Insights Externship gives you real project experience building AI-driven data pipelines.

Cryptographer / Information Security Analyst

Number theory and abstract algebra have a direct, real-world application that surprises most people: cryptography. Cryptographers design the encryption systems that protect financial transactions, government communications, and personal data.

The broader information security analyst category carries a BLS median of $120,360, with 33% projected growth. This is one of the few careers where pure math coursework (especially number theory and group theory) gives you a distinct, hard-to-replicate advantage. The NSA alone employs more mathematicians than most people realize.

Market Research Analyst

Market research analysts study consumer behavior, design surveys, run experiments, and build models that predict purchasing patterns. It's a strong entry point if you're interested in the business side of analytics but don't want to go full data science right away.

Median salary: $74,680. Growth: 13%. Consumer goods companies, tech firms, and advertising agencies hire for these roles consistently.

Biostatistician

Biostatisticians apply statistical methods to biological and health data, most commonly in clinical trials and pharmaceutical research. The work involves designing studies, analyzing patient outcomes, and ensuring regulatory compliance with agencies like the FDA.

Salaries are comparable to general statisticians (around $104K), though senior biostatisticians in pharma can earn considerably more. Fair warning: most positions do require a master's degree. But some entry-level roles at CROs (contract research organizations) accept a strong BS in math or statistics, so it's not completely closed off at the bachelor's level.

Want to build real data and analytics experience before you apply? The TruBridge Healthcare Data Analytics Externship puts you on real healthcare data projects. Or if finance is more your speed, the Yinan Zhao Investing Financial Modeling Externship gives you hands-on modeling experience with professional mentorship.

What Are the Highest-Paying Math Careers?

Math consistently ranks among the highest-paying and most AI-resilient college majors. Here's how those 12 careers stack up on compensation:

The top earners (quantitative analyst, software engineer, actuary) reward deep specialization and, in some cases, years of exam prep or advanced degrees. But look at the floor, not just the ceiling. Even the most accessible entry-level path on this list, data analyst, starts around $70K. That's well above the median starting salary for all bachelor's degree holders ($62,500, per NACE's Class of 2025 report).

One pattern worth calling out: the roles with the biggest paychecks also tend to require the most skill-building beyond your degree. And the roles with the lowest barrier to entry pay less initially but offer clear promotion paths into six-figure territory within a few years. So the question isn't really "which pays the most?" It's "which tradeoff fits your timeline?"

How Do You Get a Math Job With No Experience?

This is the part where most career guides go vague. "Network more." "Be proactive." Not helpful. Here are three things you can actually do this semester.

Turn Coursework Into Employer-Ready Language

Your transcript says "Real Analysis" and "Abstract Algebra." The hiring manager reading your resume wants to see "mathematical modeling" and "data security and encryption." Same skills, different packaging.

Here are a few translations to steal:

• Real Analysis becomes "mathematical modeling and rigorous quantitative analysis"

• Abstract Algebra becomes "encryption systems and structural pattern recognition"

• Probability Theory becomes "risk assessment and statistical forecasting"

• Linear Algebra becomes "data modeling, dimensionality reduction, and machine learning foundations"

• Differential Equations becomes "dynamic systems modeling and predictive analytics"

This isn't exaggerating. It's showing employers the connection between what you studied and what they need. Two sentences on your resume can do what your transcript can't.

Build a Quantitative Portfolio With Real Projects

Two or three completed projects prove more than a 4.0 GPA. I know that sounds like an exaggeration. It's not. Here are three ideas you can finish in a weekend:

• Kaggle competition entry. Pick a beginner competition (housing prices, Titanic survival), build a model in Python, and write a short analysis of your approach. Even a mid-ranking submission proves you can work with real data.

• Actuarial case study. Download public mortality or insurance claims data, calculate basic risk metrics, and present your findings in a short report. This mirrors the exact workflow actuarial employers want to see.

• Financial model. Build a DCF (discounted cash flow) model for a public company using SEC filing data. Walk through your assumptions in a write-up. Financial analysts do this daily.

Use Externships to Get Real Experience Fast

No internship lined up? Externships offer a faster path to real professional experience. These are structured 8-week programs where you work on actual company projects with professional mentorship, all remote.

For math majors specifically, Externships in data analytics and financial modeling let you apply your quantitative skills to real business problems. That's the kind of resume-ready experience that makes interviewers actually lean forward. It's more compelling than any classroom assignment, and you can complete one during a regular semester.

Explore data, finance, and analytics Externships →

Do You Need a Graduate Degree for Math Careers?

It depends on which path you pick. Here's the honest breakdown:

A bachelor's degree is enough for:

• Data analyst

• Financial analyst

• Operations research analyst (entry-level)

• Market research analyst

• Actuary (with exam progress)

• Software engineer (with coding skills)

A master's or PhD is typically expected for:

• Quantitative analyst (especially at top firms)

• Biostatistician

• Data scientist (at research-heavy organizations)

• Machine learning engineer (at top-tier companies)

• Academic positions (professor, researcher)

Here's what I'd actually recommend, though. Don't decide right now. Many math graduates start in a bachelor's-level role, gain two to three years of experience, and then pursue a graduate degree with employer sponsorship or a much clearer sense of which specialization they want.

Rushing into a master's program straight out of undergrad often means paying full tuition for a degree you could have gotten funded two years later. That's not always a mistake, but it's worth thinking about before you default into it.

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What About Math Career Paths Outside Academia?

If you're a math major, you've probably lost count of the number of times someone's asked, "So... you're going to be a teacher?" It's one of the most persistent (and most wrong) assumptions about the degree.

Fewer than 15% of math bachelor's degree holders end up in education or academia, according to the American Mathematical Society's annual survey. The other 85%? They're scattered across five major industry clusters:

• Financial services. Banks, insurance companies, hedge funds, and fintech startups all hire math graduates for risk management, modeling, and analysis roles.

• Technology. Google's search algorithms, Spotify's recommendation engine, every ML model your phone runs in the background. Math underpins all of it. Companies hire math majors for data science, engineering, and product analytics.

• Consulting. McKinsey, BCG, and Bain actively recruit math majors because structured problem-solving translates directly to client work.

• Government and defense. The NSA is one of the largest employers of mathematicians in the country. The Census Bureau, Federal Reserve, and intelligence agencies all need quantitative talent too.

• Healthcare and pharma. Clinical trial design, epidemiological modeling, health economics. If the work involves statistics and human health, there's a math major doing it somewhere.

The "math is too theoretical for the real world" myth doesn't survive contact with actual employment data. Your degree doesn't lock you into one path. It's a foundation that works almost everywhere.

How to Start Your Math Career Path Today

Reading about career paths is useful. But nothing happens until you take a step. Here are two things you can do this week.

Pick a Target Industry and Research What They Actually Want

Go to the BLS Occupational Outlook Handbook and read the full profile for two or three roles that interest you. Then open LinkedIn, search for those job titles, and read 10 recent postings. Pay attention to which tools, certifications, and experience levels keep coming up.

This takes about an hour. And it gives you a dramatically clearer picture of what to prioritize than reading one more Reddit thread ever will.

Build Experience Before Graduation

You've got more options than you think:

• Externships. Complete a real project for a company like Amazon, TruBridge, or Breaking Games through Extern's structured 8-week programs. You'll get professional mentorship, a portfolio piece, and a credential for your resume. Browse current Externships →

• Research assistantships. Ask your math or statistics professors if they need help with research. Even unpaid work builds your analytical portfolio.

• Actuarial exam prep. If actuarial science interests you, start studying for Exam P/1 now. Passing even one exam before graduation signals serious commitment to employers.

• Kaggle or open-source contributions. Build public proof of your technical skills. Recruiters do check GitHub profiles and Kaggle rankings. It's not a myth.

Your math degree gives you the foundation. What you build on top of it, starting today, determines which doors open first.

FAQ

Is a math degree worth it in 2026?

Short answer: yes. Math occupations are on track to grow 21% through 2034, more than four times the national average. Starting salaries for math graduates fall between $65K and $75K, with mid-career medians clearing $100K in most quantitative paths. Few other majors offer that combination of demand and earning potential.

What entry-level jobs can I get with just a bachelor's in math?

Data analyst, actuarial assistant, financial analyst, operations analyst, and junior software developer are all accessible with a BS. These employers value quantitative training over industry-specific experience, especially when you can show applied projects or an Externship credential on your resume.

Is a math degree harder than an engineering degree?

They're different kinds of challenging. Math leans more abstract and proof-based. Engineering is more applied and project-driven. Neither is universally harder. But math majors tend to develop stronger theoretical foundations, which transfer broadly across careers in data, finance, and tech.

Can math majors work in finance without a finance degree?

Absolutely. Financial analyst, quant, and risk management roles actively recruit math graduates because the modeling skills transfer directly. Plenty of Wall Street firms actually prefer math or physics backgrounds for their most quantitative positions over traditional finance or accounting degrees.

What's the job outlook for math careers through 2034?

Strong across the board. The BLS projects roughly 56,000 new math-related positions by 2034. Data science, actuarial work, and operations research are growing fastest. The common thread is that every industry increasingly needs people who can work with data and models at a deeper level than basic spreadsheet analysis.

Do employers hire math majors for data science roles?

Yes, and the trend is accelerating. Math graduates bring the statistical theory and modeling fundamentals that data science depends on. Most hiring managers care more about your Python or R proficiency and your project portfolio than whether your diploma literally says "data science."

What can I do with a liberal arts math degree?

A BA in mathematics qualifies you for the same core career paths as a BS. You might need to supplement with coding coursework or a technical certification depending on the role, but data analyst, market research analyst, and actuarial positions are all strong entry points that don't require a BS specifically.