To become a quant, build a strong base in probability, statistics, linear algebra and calculus, learn to code well in Python (plus C++ for many roles), and pick one target role: quant researcher, quant trader or quant developer. Most people get in through a quant internship or a graduate program, after a math-heavy degree or a quant master's, and recruiting starts 12 to 18 months before the start date. Expect a resume screen, an online assessment and several rounds of technical interviews.
I'm Fiona Taft, founder of QuantMinds, former Executive Director of UC Berkeley's MFE program and former Associate Director at Stanford University. The guidance here is drawn from my recorded webinars on quant recruiting. Quotes from my webinars are lightly edited for clarity. Other facts are linked to their sources.
What a quant is
A quant, short for quantitative analyst, uses math, statistics and programming to make decisions in financial markets: valuing securities, finding trading signals, building portfolios and measuring risk. The US Department of Labor's O*NET database lists the job as Financial Quantitative Analysts and describes tasks such as applying math and statistics to derivative valuation, building model libraries, and supporting researchers and traders.
Quants work at hedge funds, proprietary (prop) trading firms, asset managers and banks.
The main quant roles
In my quant finance career AMA, I described the core split this way: "A quant researcher is going to be someone who designs the models. You're going to be creating the models. And then the quant trader is going to be the one implementing the models." If you are unsure which fits, read QR, QT or QD: which quant path is right for you.
Quant researcher (QR)
Quant researchers build the models behind trading and investment decisions: forming an idea, testing it on historical data, then refining or discarding it. Firms screen for deep probability and statistics, research experience and strong Python. This is where a PhD is most at home.
Quant trader (QT)
Quant traders use models and fast judgment to make trading decisions and manage positions and risk. I point people toward this role if they want a very fast-paced environment and are good at brain teasers, quick math and poker, and a master's is often a feeder into it. At some prop trading firms, research and trading are one hybrid role.
Quant developer (QD)
Quant developers are the engineers who build the systems and infrastructure that run the strategies. That means production code, often C++ where speed matters and Python elsewhere, plus data pipelines. Firms screen for software engineering skill, fluent coding and data handling.
Quant risk, model validation and quant analyst roles
Banks also hire quants to measure risk and to check other teams' models, and I include quantitative risk among the areas candidates should target. Model validation has a regulatory basis: US banking regulators' revised model risk guidance (SR 26-2, April 2026) describes validation as evaluating whether models perform as expected, including their reliability and limitations. These roles screen for the same math and coding, plus clear writing.
Buy side vs sell side: where quants work
The sell side is the big banks. Their quant teams include desk quants, quant strats, model validation and quant risk, and banks run formal internship and graduate programs. The buy side trades or invests capital. I contrast it with the banks this way: "On the other side, we have buy-side firms ... These are going to be hedge funds, prop trading firms, asset managers, systematic firms, high frequency trading, and so forth. They have smaller teams, and they are more selective."
What this means for a newcomer:
- Banks hire on structured cycles, while buy-side firms hire on rolling applications and take fewer people, so apply early.
- Prop trading firms often hire people without a finance background. Jane Street's interviewing page, for example, says it does not test candidates on finance or economics knowledge.
- Systematic asset managers can be friendly to PhDs who want to move into quant.
I see a bank as a strong first step: "Going to the sell side for a year or two, and then transitioning to the buy side is a really good pathway. A lot of the firms look very favorably on those who have been at big banks because of the amount of training that you get." I also advise applying to both sides, with a resume focused on one role. More detail is in Buy side, sell side, or prop shop? A realistic entry guide.
The skills you need
Math
I set out the technical foundation this way: "You're going to have a few different areas, and one is going to be your technical foundation: probability, stats, linear algebra and calculus, including multivariable calculus, stochastic calculus, stochastic processes and derivatives, and definitely programming."
- Probability and statistics: reasoning about uncertainty and testing whether a pattern in data is real or luck.
- Linear algebra: working with many assets and data series at once, as in regressions.
- Calculus, through multivariable: optimization, and the base for everything after it.
- Stochastic calculus and stochastic processes: the math of values that move randomly over time, used to value derivatives.
How much you need depends on the role. See the math you need to break into quant finance.
Programming
My bar is fluent Python at minimum and, ideally, intermediate to advanced C++. Python, with libraries such as NumPy and pandas, is the everyday tool for research and data work. C++ runs systems where speed matters. SQL pulls data, and R and MATLAB appear on some teams. For the Python bar by role, read Python for quant roles: what matters.
Soft skills
Firms want people who can explain highly technical work to someone who is not technical. They also want openness to feedback: a candidate who insists their way is the only way will be rejected.
Education paths
Undergraduate majors
There is no single required major. My list: math, probability, statistics, financial engineering, computer science, data science, engineering and other math-heavy sciences.
When a master's helps, and when it does not
Common quant master's degrees include the MFE (Master of Financial Engineering), the MFin (Master of Finance) and the MSCF (Master of Science in Computational Finance). It is possible to land at top quant firms straight from undergrad, especially from a top-brand university, but the best way in is often through a master's.
On the limits, I put it this way: "The other myth is that a Master's guarantees a quant job. No, that is incorrect. It opens doors. It is an edge, but it's not necessarily guaranteed." A master's helps most if you are switching fields or need to close math or coding gaps. It adds least if you already have the skills and projects firms screen for. To compare programs, read our guide on how to choose a quant master's program, or watch the replay of Do You REALLY Need a Master's to Land in Quant?
A PhD for research
A PhD is the natural route into quant research. Many firms post positions for PhDs, there are not enough interested PhDs to fill the buy-side roles, and firms often open those roles to master's candidates too.
The recruiting timeline
Quant recruiting runs early. As I put it: "The recruitment clock does run early in quant: 12 to 18 months ahead of time. Buy side firms are on rolling applications. Banks tend to have structured cycles."
In the cycle I describe:
- Graduate roles open around June and July and close in October.
- Internship applications tend to close in late October.
- January to June is a busy hiring stretch, but much of it is just-in-time hiring for immediate needs.
The most realistic path into a full-time offer is an internship return offer or a graduate program. Waiting until you graduate to apply is too late. See the replay of Are You Behind the Curve for Full-Time Graduate Recruiting?
The hiring process, step by step
Here is the sequence I describe:
- Resume screen. A clean format that lets the recruiter see quickly who you are.
- Online assessment. A timed technical test covering mental math, probability, statistics and coding. A lot of firms use HackerRank.
- HR interview. Some firms hold it before the assessment. Together, these two make up the first round.
- Technical interviews. Deeper rounds on math, probability, coding and your projects.
- Superday. A final round of several interviews, online or in person.
- Offer.
Expect about 4 to 8 weeks of interviews for an internship and 6 to 8 weeks for a graduate role. I walk through each stage in my AMA on quant campus recruiting.
How to prepare for quant interviews
- Mental math. My rule: "If you haven't been practicing your mental math, that's definitely something you should be doing on a regular basis, setting aside 30 to 60 minutes a day."
- Probability, statistics and brain teasers. I recommend studying A Practical Guide to Quantitative Finance Interviews, known as the Green Book.
- Coding. I recommend LeetCode and HackerRank. A free HackerRank account gets you used to the platform many firms test on.
- Behavioral questions. Prepare and polish answers to the standard questions: tell me about yourself, walk me through your resume, tell me about your projects, and why should we hire you for this role at this firm.
For the order to prepare in, read why most quant prep is backwards.
Resume, LinkedIn and cover letter
Resume. Use no columns and no graphics. My order: education with GPA, skills, employment history, projects, then interests. Put the key items in the top half, since recruiters often give a resume about six seconds. Show evidence: impact statements, outcomes, projects and competitions. See why your quant resume isn't getting responses.
LinkedIn. Recruiters and headhunters search LinkedIn, so spell out what you want in your headline with terms such as quant research, data-driven and Python. Read how to use LinkedIn to get a quant job.
Cover letter. Keep it to half or three-quarters of a page. Cover why this firm, why this role and why you are the best candidate. The replay of What You Need to Do NOW to Land a 2027 Summer Quant Internship covers all three documents.
Networking
Cold applications can work with a strong resume and cover letter, but referrals and recommendations count for a great deal at quant firms. Referrals come from relationships, not one-off requests. As I explain it: "Alumni don't want to have these transactional relationships where you reach out once and ask for a referral. You need to establish that relationship before you ask for that referral, and you should be meeting with that contact anywhere from 2 to 4 times within 6 to 12 months."
- Always add a message to a connection request.
- Ask for a 10 to 15 minute coffee chat.
- Do not ask for a job or a referral in your first message. Ask for advice, and offer your own insight.
A step-by-step plan by stage
If you are an undergraduate
- Take the core math early: multivariable calculus, linear algebra, probability and statistics.
- Get fluent in Python. Add C++ for development or trading.
- Build projects, enter trading competitions, and join a student investment fund if your school has one.
- Pick one target role and tailor your resume to it.
- Apply for internships 12 to 18 months ahead, on both sides.
- Build alumni relationships months before you need a referral.
If you are a master's student
- Have your resume and LinkedIn ready before the program starts. On a one-year program, recruiting may start almost as soon as you arrive.
- Practice for online assessments daily.
- Use your program's career staff, alumni and classmates.
- Apply for internships and graduate roles as soon as they open.
If you are switching careers
If you lack coding or a technical background, you will need to upskill first. One way to do that is a master's, which also keeps graduate roles open to you. I explain why this way: "These grad roles are meant for individuals who have 0 to 2 years of experience in the field. Maybe you have prior experience, but you went back to school to get your master's: you are still considered a grad. You are eligible to apply for these roles." Aim first at the role closest to your current skills: a software engineer toward quant development, a statistician or data scientist toward research or risk.
If you are at a non-target school
A non-target school is one where quant firms do little or no on-campus recruiting. My answer to getting noticed is your projects, past experience, research and technical skills. A student fund and steady alumni outreach help, and a master's can give you a second shot at a top brand. Read how to compete with elite-school candidates without the pedigree.
Common mistakes
- Applying to every role type at once. My warning: "Do you know if you're targeting QR, QT or QD? If you apply for all three, many firms will reject you, because they want to know that you've applied to just a QR role, a QT role or a QD role."
- Saving links to apply later. By the time you graduate, the graduate roles are filled.
- One resume for every job, or a bot applying for you. Tailor the resume to the exact role.
- A narrow target list. Apply broadly across buy side and sell side, with a focused resume.
- Listing a project you cannot talk about yet. Recruiters ask about anything on your resume, so add a project once you have done enough real work to discuss it.
- Connection requests with no message. This is a big mistake: people click connect and hope someone accepts.
How hard is it to become a quant?
It is hard, for specific reasons. Buy-side teams are small and selective. The process has several rounds, including timed tests. You need math, coding and communication at once, and recruiting runs a year or more ahead, so a late start can cost a full cycle.
It is also more open than it looks. Banks run formal programs. Risk, model validation and quant development roles are real entry points. Some trading firms do not require a finance background. Most of what firms screen for, from mental math to coding and a clean resume, improves with steady practice over months, not weeks.
Frequently asked questions
What is a quant?
A quant, or quantitative analyst, uses math, statistics and programming to value securities, find trading signals, build portfolios or measure risk. Quants work at hedge funds, prop trading firms, asset managers and banks.
What does a quant do?
Researchers design and test models, traders put them into practice, developers build the systems that run them, and risk and validation quants check that models behave as expected.
What does a quant trader do?
A quant trader uses models and fast judgment to make trading decisions and manage positions and risk. It suits people who like a fast pace and are good at quick math and brain teasers.
What is a quant developer?
A quant developer is the engineer who builds the systems and infrastructure that run trading strategies. The role needs strong C++ and Python and solid data handling.
How hard is it to become a quant?
It is competitive: small buy-side teams, several interview rounds and early recruiting. Most of what firms test, such as mental math, probability and coding, improves with months of steady practice.
How do I get into quant finance?
Build the math and Python base, pick one target role, and apply for internships and graduate programs 12 to 18 months ahead on both sides. Pair that with a tailored resume and alumni networking.
Can I break into quant without a finance background?
Yes. Prop trading firms often look for students without a finance background. Jane Street's interviewing page, for example, says it does not test candidates on finance or economics knowledge.
Get a second opinion
If you want a second opinion on your plan, you can request a free Discovery Session, a Zoom session with one of our coaches: quantminds.com/discovery-session-request.