How to become a Senior Data Scientist

1. 1

   Understand the role

   First, read the Senior Data Scientist job profile: missions, typical day, context, expected soft skills. That's what tells you if the role suits you, beyond salary.

2. 2

   Build the key skills

   Core technical skills are listed below. Don't try to master them all at first: aim for 3 or 4 "core" skills truly mastered, the rest will come with practice.

3. 3

   Choose your education path

   Several paths: engineering school (3 to 5 years), intensive bootcamp (3 to 6 months), state-funded training (CPF in France), or self-taught with a strong portfolio. The diploma matters less than the proof: projects, GitHub, certifications.

4. 4

   Build a portfolio

   2 to 3 concrete projects that demonstrate the key skills. For tech profiles: public code on GitHub, deployed app. For non-tech profiles: case studies, real deliverables with context / problem / solution / result.

5. 5

   Land a first role

   Target: an internship / apprenticeship / junior FTE in a team that mentors. A learning role beats a prestigious title. Track your applications so you don't lose the thread.

6. 6

   Grow over 3 to 5 years

   Junior → Senior → Lead. Key milestones: measurable impact, mentoring, ownership on strategic projects, technical and product vision. These signals make the difference in promotion reviews.

Hard skills to aim for

Knowledge to master

Plan your career

With Traject, structure your steps, track your applications, and learn from proven templates.

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