Data Scientist
Paris-based AI company building frontier models, AI applications, developer tools, and compute infrastructure for enterprise and public-sector deployments.
About Mistral AI
Mistral AI develops open-weight and commercial language models and provides a full-stack AI platform spanning agents, application development, custom-model training, APIs, and AI cloud infrastructure.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will define product metrics, analyze AI product performance, and identify improvement opportunities. You will design experiments, build end-to-end data science projects, evaluate models in training and production, develop user-satisfaction frameworks, and work with engineering to ensure accessible, high-quality data.
Requirements
- Proficiency in Python and SQL
- Product acumen
- Experience extracting insights from large, complex data
- Statistical intuition
- Experience with experimental design, causal inference, and machine learning algorithms
- Ability to explain technical concepts to non-technical audiences
Responsibilities
- Define key metrics and analyze AI product performance
- Identify product improvement opportunities
- Design and analyze experiments, including A/B tests and causal inference
- Implement end-to-end data science projects
- Evaluate model performance in training and production
- Identify edge cases and develop user-satisfaction measurement frameworks
- Work with engineering to ensure data quality and accessibility
- Mentor peers and share data science and analytics practices depending on seniority
Benefits
- Healthcare coverage
- Parental leave
- Retirement plans
- Relocation support
- Wellness programs
- Meal allowances
- Transportation allowances
- Location-specific perks
Hiring Process
Introductory recruiter call; hiring manager interview; Python and statistics/machine-learning technical interview; homework assignment and review presentation; value talk interview; references.