Resume example 2026
Data Scientist resume: template, ATS keywords, mistakes to avoid
The complete guide to building a Data Scientist resume that passes ATS filters and holds recruiters' attention.
The essential point: La valeur d'un Data Scientist ne se mesure pas à la complexité de ses modèles, mais à la décision qu'ils changent. Un modèle à 99 % de précision jamais mis en production vaut zéro. Les meilleurs savent dire « un simple seuil suffit ici » plutôt que sortir l'artillerie deep learning.
Recommended resume structure
Recruiters scan a Data Scientist 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 Scientist title (or equivalent: Scientifique des données, Data Scientist ML), 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 Scientist: Explorer et nettoyer des ; Construire des features pertinentes ; Entraîner, évaluer et comparer...
- 4
Education
Prioritize the most recent and most recognized degree. For a Data Scientist, the most valued credentials are: École d'ingénieur (option data/IA), Master Data Science / Maths appliquées.
- 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 Scientist, this is often what sets two equivalent junior profiles apart.
The 11 ATS keywords to include in your Data Scientist resume
These are the keywords that ATS (Workday, Greenhouse, Taleo…) scan in Data Scientist 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 Scientist resume
These are patterns we see constantly that disqualify a resume in 3 seconds. Check each one before you send.
Empiler les algorithmes sans jamais relier au résultat business
Ne montrer aucun modèle réellement mis en production
Passer sous silence le travail de data quality (80 % du métier)
Multiplier le jargon sans une métrique d'impact claire
The 5 classic interview questions for Data Scientist
If you land an interview, prepare concrete answers for each of these questions. Use the STAR framework: Situation, Task, Action, Result.
- 1
« Explique le compromis biais-variance avec un exemple concret. »
- 2
« Comment tu expliques un modèle de scoring à un directeur non-technique ? »
- 3
« Ton dataset est très déséquilibré (1 % de positifs). Tu fais quoi ? »
- 4
« Comment tu détectes qu'une feature provoque une fuite de données (data leak) ? »
- 5
« Ton A/B test n'est pas significatif. Quelles décisions tu prends ? »
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