Resume example 2026
Data Analyst resume: template, ATS keywords, mistakes to avoid
The complete guide to building a Data Analyst resume that passes ATS filters and holds recruiters' attention.
The essential point: La différence entre un bon Data Analyst et un excellent, c'est la capacité à poser la BONNE question avant de chercher la réponse. Maîtriser SQL, c'est le ticket d'entrée. Savoir dire 'non, cette métrique ne mesure pas ce que vous pensez' — c'est ce qui te fait progresser.
Recommended resume structure
Recruiters scan a Data Analyst resume in 7 seconds on average. The top third must carry 80% of the signal. Here is the order that works best for this job:
- 1
Header
First name + last name, Data Analyst title (or equivalent: Analyste de données, Business Analyst data), email, phone, LinkedIn, city.In France: no mandatory photo, no age, no family status.
- 2
Professional summary (3-4 lines)
The hook — what you do, for whom, with what standout result. Avoid empty adjectives ("passionate", "dynamic"). Place 2-3 priority ATS keywords here.
- 3
Professional experience
The most-read section. Each experience follows the STAR structure: Situation / Task / Action / Result. Prioritize the responsibilities tied to the target job posting.
- • 3-5 bullets per role maximum
- • Each bullet: action verb + object + quantified result
- • Typical responsibilities for a Data Analyst: Écrire des requêtes SQL ; Construire et maintenir des ; Analyser des A/B tests...
- 4
Education
Prioritize the most recent and most recognized degree. For a Data Analyst, the most valued credentials are: Master Statistiques / Data Science, École de commerce avec spé data/finance.
- 5
Technical skills
A precise, categorized list (technical / tools / languages). Avoid percentage charts: ATS don't read them.
- 6
Certifications & projects (optional)
Recognized certifications, published personal projects (GitHub, portfolio, blog). For a Data Analyst, this is often what sets two equivalent junior profiles apart.
The 11 ATS keywords to include in your Data Analyst resume
These are the keywords that ATS (Workday, Greenhouse, Taleo…) scan in Data Analyst resumes. Naturally including half of them significantly improves your chances of passing the first automatic filter.
Caution: don't copy the whole list. Only include keywords for which you have real experience — a recruiter who reads "SAP" expects you to be able to discuss it.
The 4 fatal mistakes on a Data Analyst resume
These are patterns we see constantly that disqualify a resume in 3 seconds. Check each one before you send.
Ne pas préciser la taille des datasets manipulés (100 lignes vs 100 millions, c'est différent)
Confondre 'créer un dashboard' et 'apporter un insight qui a changé une décision'
Oublier de mentionner les outils exacts (Looker ≠ Looker Studio)
Pas assez de chiffres d'impact (taux de conversion amélioré, budget influencé)
The 5 classic interview questions for Data Analyst
If you land an interview, prepare concrete answers for each of these questions. Use the STAR framework: Situation, Task, Action, Result.
- 1
« Raconte-moi une analyse dont tu es particulièrement fier. Quel a été son impact réel ? »
- 2
« Comment tu expliquerais l'intervalle de confiance d'un A/B test à un manager non-technique ? »
- 3
« Tu dois calculer le taux de rétention des utilisateurs : comment tu définis le numérateur, le dénominateur, la fenêtre temporelle ? »
- 4
« Tu reçois un dashboard où les chiffres ne collent pas avec ton intuition. Comment tu procèdes ? »
- 5
« Explique la différence entre INNER JOIN et LEFT JOIN avec un exemple concret. »
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