Selective Quant Resume Strategy

Reviewed by Fallon Han· Updated 2026-06-01 06:06:45.974

This conversation was generated using Cook'd AI's career assistant and reviewed by Fallon Han from our editorial team for accuracy.

I'm a final-year math student in Germany with an EU passport, and I'm applying to quant trading firms and prop shops. Can you help me decide which classes, competitions, and projects should stay on my resume and which ones I should remove? I want it to look more selective and aligned with the roles.

Yes. For these roles, your resume should signal three things fast: strong math, coding ability, and evidence you can work on fast, data-heavy problems. Keep the items that prove that directly, and cut anything that looks broad, academic, or generic. Keep: - Advanced probability, stochastic processes, optimization, statistics, numerical methods - Any serious programming coursework if it involved Python, C++, algorithms, or data structures - Trading, quant, or market-related competitions - Projects with backtesting, forecasting, signal research, simulation, or low-latency coding - Strong rankings, awards, or selective admissions if they are competitive and relevant Remove or de-emphasize: - Purely theoretical classes that do not add signal for trading roles - General coursework lists with too many modules - Projects that are not quantitative, not technical, or not finished - Competitions that were broad, non-selective, or unrelated to finance or problem solving - Basic class assignments that do not show initiative A good test is: would a recruiter at a prop shop care in 10 seconds? If not, cut it or compress it heavily.

That makes sense. I have classes like real analysis, measure theory, abstract algebra, numerical linear algebra, stochastic calculus, and optimization. Should I list all of them, or only some? I also have a few programming classes but nothing super advanced.

Do not list all of them. For your target, a compact and selective math stack is better than an exhaustive transcript-style list. Prioritize these on the resume: - Stochastic calculus - Optimization - Numerical linear algebra - Probability and statistics if you took them - Any machine learning, scientific computing, or algorithms course with real coding work Usually de-emphasize or omit: - Real analysis - Measure theory - Abstract algebra Those are strong academically, but they do not add much direct trading signal unless you need one line to prove overall rigor. If you keep one or two, place them under a short line like Relevant Coursework and do not make it look like a full degree audit. For programming classes, only keep them if they involved practical implementation in Python or C++. If they were mostly theory, compress them into a short mention such as Python, C++, SQL, algorithms, and data structures.

I also did an extracurricular trading competition, a math modeling contest, and a personal project where I built a Monte Carlo pricing tool in Python. I feel like all three are useful, but my resume is getting crowded. Which ones should stay?

Keep all three only if each one adds a different kind of signal. If space is tight, rank them by relevance and strength. Best to keep at full detail: - Monte Carlo pricing tool in Python, because it shows direct quant work, coding, and financial modeling - Trading competition, if it was selective and you can quantify your ranking or results Potentially compress or cut: - Math modeling contest, unless it was highly selective, national, or had a strong quantitative finance angle How to present them: - Put the Monte Carlo project first and make it concrete: pricing models, simulation, variance reduction, validation, speed improvements - For the trading competition, include rank, team size, and strategy focus if any - For the math contest, only keep it if it has a recognizable name or a strong placement. Otherwise, it can become a single-line bullet or be removed The resume should not read like a list of everything you ever did. It should read like you deliberately built a profile for quant trading.

Should I mention my thesis? It's on a pretty theoretical topic in probability. Also, I have part-time tutoring experience in calculus and linear algebra. I worry both may be irrelevant, but I don't want to look empty.

Use both only if you frame them carefully. Thesis: - Keep it if you can connect it to stochastic modeling, inference, or optimization - If it is very theoretical, include it in one line only and avoid dense academic wording - Example angle: Final-year thesis on probability theory with emphasis on rigorous stochastic methods Tutoring: - Keep it only if you need one more line and there is no stronger experience available - Do not make it the focus - If you include it, emphasize transferable skills: explaining complex ideas clearly, managing deadlines, working with high-performing students For your target, the resume should not try to prove you are a tutor. It should prove you are a future quant. So if space is tight, thesis stays before tutoring. Tutoring can be cut if your project and competition section are already strong.

Can you suggest how I should rewrite the top half of the resume so it looks more selective? Right now it feels like a general math student resume instead of something for prop shops.

Yes. The top half should be optimized around signal density. Recommended structure: 1. Header with name, Germany, EU passport if relevant for work eligibility, email, GitHub, LinkedIn 2. One-line summary focused on quantitative trading and programming 3. Education with only the most relevant coursework 4. Experience or Projects, with the strongest quant project first 5. Competitions and achievements, only the most selective ones Rewrite your summary to sound narrower and more intentional. Example: Final-year mathematics student with strong probability, optimization, and Python skills, building quantitative models and simulation tools for trading-oriented applications. Then make the first bullets do the work: - Built Monte Carlo pricing tool in Python to estimate option values and test convergence behavior - Applied stochastic methods and numerical optimization in coursework and independent projects - Competitive placement in a trading or modeling contest, if applicable Also remove anything that weakens the positioning, such as long hobby lists or broad unrelated internships. The goal is to look like someone who applied math to markets on purpose, not someone who is simply good at math.