How is a finance CV scored?

Your CV is scored 0–100 across six weighted criteria: metrics & quantification (25%), bullet point quality (20%), role-fit alignment (20%), structure & formatting (15%), education (10%), and skills & keywords (10%). Each is benchmarked against successful candidates at firms like Goldman Sachs, Citadel, and KKR.

Is this just generic CV advice?

No. Every point is specific to your CV — it quotes your actual bullets and explains exactly why each one is weak. The rubric also adapts to your target role, so an investment banking CV and a quantitative research CV are judged against entirely different criteria.

How is this different from my university careers service?

Careers services give general guidance like "use strong verbs". This gives you firm-specific feedback: your exact bullets rewritten in top-tier analyst voice, the precise ATS keywords your CV is missing, and a ranked action plan — all benchmarked to bulge-bracket and top-fund standards.

How long should a finance CV be?

One page for students and recent graduates; up to two pages once you have a few years of relevant experience. Bulge-bracket recruiters treat a two-page student CV as a red flag — fitting everything onto one page is itself part of the test.

What do I get for £19?

The full report: a scored breakdown of all six sections, three of your weakest bullets rewritten in top-firm voice, a role-specific list of missing keywords, a ranked action plan, and a benchmark against a successful candidate at your target firm tier. The score preview is always free.

How much does a finance CV review cost?

Professional CV writers and careers consultants typically charge £100–400, and university careers services are free but give generic feedback. Finance CV Audit gives you a finance-specific score for free, and the full report — your CV rewritten, missing keywords, a ranked action plan, and a recruiting guide — for a one-time £19.

Is there a money-back guarantee?

Yes — a 30-day, no-questions-asked money-back guarantee. If the full report does not help you improve your CV, email us within 30 days and we will refund the £19 in full.

Is my CV kept private?

Yes. Your CV is analysed in real time and is not stored after the analysis, never sold, and never shared for marketing. We keep only the email you provide to send your report and a short series of follow-up tips, which you can unsubscribe from at any time. See our Privacy Policy for full detail.

What file types do you support?

PDF and Word (.docx), up to 10MB. The PDF must be text-based rather than a scanned image, so the analysis can read your actual CV text. Upload takes about five seconds.

16 June 2026·8 min read

Quant Finance CV Guide: How to Write a Quantitative Analyst CV

How to write a quant finance CV for roles at Jane Street, Citadel, Two Sigma and beyond — the technical specificity, projects, and keywords that get a quantitative analyst CV shortlisted.

Quant recruiting is the most technically demanding in finance, and the CV screen reflects it. Firms like Jane Street, Citadel, Two Sigma, and DE Shaw are looking for genuine mathematical ability, real coding skill, and evidence you can do research — not buzzwords. A quant CV lives or dies on specificity and proof.

What quant firms actually screen for

Three things: demonstrable technical ability (maths, statistics, CS), the tools to apply it (Python, C++, R), and evidence you have actually built something. A CV that says “strong analytical skills” and “proficient in data analysis” is invisible. The screen rewards precision.

Specificity is everything

Replace generic claims with exact tools and methods. Not “programming,” but Python (pandas, NumPy, scikit-learn) and C++. Not “statistics,” but the methods you have actually used — regression, time-series, Monte Carlo, hypothesis testing. Name versions of the truth a reviewer can probe.

Weak

Used data analysis and machine learning to study financial markets.

Strong

Backtested a momentum signal on 10 years of equity data in Python (pandas, NumPy), achieving a Sharpe of [X] after transaction costs; documented the methodology and code on GitHub.

Projects are your proof

For quant roles, projects often carry more weight than work experience. A public GitHub repository, a Kaggle competition placing, an open-source contribution, a maths-olympiad background, or published research are all concrete, verifiable evidence of ability. Link them — a reviewer who can click through to real code is far more likely to advance you.

Education

Lead with your quantitative degree (maths, physics, statistics, CS, or engineering), classification or GPA, and relevant modules (stochastic processes, machine learning, numerical methods). A PhD, master’s, or olympiad medals belong prominently — they are exactly the signals top quant funds recruit on.

The keywords that matter

Weave in the real vocabulary of the field: backtested, signal, factor, Sharpe, regression, Monte Carlo, feature engineering, cross-validation, stationarity. Use them where they are true — never as a list.

Common mistakes

Vague, non-technical language (“data analysis,” “analytical skills”).
No links to code or projects — claims without proof.
No quantified results on models or signals.
Listing languages without depth (“Python” with nothing built in it).

Ready to test it? Select Quantitative Research as your target role and get a free CV score — the rubric switches to quant-specific criteria, so it checks for exactly what these firms screen on.