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Mistral AI

Open-weight LLMs and enterprise AI deployment

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeÎle-de-France, FranceNo salary listedIn-person

About the Job

Requirements

  • Proficiency in Python and SQL.
  • Strong product acumen alongside technical expertise.
  • Experience extracting insights from large and complex datasets and summarizing findings for product and engineering teams.
  • Strong statistical intuition and experience with experimental design, causal inference, and machine learning algorithms.
  • Ability to explain complex technical concepts to non-technical audiences.

Responsibilities

  • Define key metrics, understand the performance of AI products in depth, and identify opportunities for improvement.
  • Design and analyze experiments, including A/B tests and causal inference, to validate hypotheses and guide product decisions.
  • Design and implement end-to-end data science projects, from data collection and preprocessing through model building, evaluation, and deployment.
  • Evaluate model performance in training and production, identify edge cases, and develop frameworks to measure user satisfaction.
  • Work with engineering to ensure data quality and accessibility for analytics and machine learning.
  • Depending on seniority, mentor peers and share best practices in data science and analytics.

Desired Qualifications

  • Curiosity about data and AI and interest in exploring new ways to use data.

About the Company

Mistral AI

Open-weight LLMs and enterprise AI deployment

Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.

Company size
1,001-5,000
Company stage
Series D
Total funding
$7.2B
Headquarters
Paris, France
Founded
2023

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