Data Scientist

Mistral AI
Paris, France
27 days ago
Apply on fr.indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Data Analysis Python (Programming Language) Machine Learning Software Product Management SQL Databases

Job description

We are seeking skilled and motivated Data Scientists to join our team in Paris. You will work at the intersection of product, research, and engineering. You will analyze user behavior, optimize product performance, and design data-driven features that enhance our AI product suite. This role is ideal for someone who thrives in a dynamic environment, enjoys tackling ambiguous problems, and wants to influence our product roadmap directly. The ideal candidate will have a strong background in data analysis, statistical modeling and machine learning, with a proven track record of delivering high-quality results in a fast-paced environment. If you’re passionate about data, curious about AI, and eager to shape the data science strategy and make an impact, this is the role for you.

What You Will Do

  • Define key metrics, understand in-depth the performance of our AI products, and identify opportunities for improvement.

  • Design and analyze experiments (A/B tests, causal inference) to validate hypotheses and guide product decisions.

  • Design and implement end-to-end data science projects, from data collection and preprocessing to model building, evaluation, and deployment.

  • Evaluate model performance in training and production, identifying edge cases, and develop frameworks to measure user satisfaction.

  • Work with engineering to ensure data quality and accessibility for analytics and ML.

  • Depending on seniority, mentor peers and share best practices in data science and analytics.

Requirements

  • Proficiency in Python as well as SQL.

  • Highly technical but with a strong product acumen.

  • Experience in extracting insights from large and complex data, summarizing findings and sharing takeaways for product and engineering teams.

  • Strong statistical intuition and experience with experimental design, causal inference and machine learning algorithms.

  • Excellent communication and ability to explain complex technical concepts to non-technical audiences.

  • Creative, curious, and innovative-you love exploring new ways to use data.

Hiring process

  • Intro call with Recruiter (30 min)

  • Hiring Manager Interview (30 min)

  • Technical interview - Python + Stats/ML (60 min)

  • Homework Assignment (5-day prep) + Review Presentation (60 min)

  • Value talk interview (30 min)

Benefits & conditions

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.

About the company

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems-across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector-co-creating customized AI systems that they can run on their terms.

We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on fr.indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

54 sec

Generating multiple hook options for outreach A/B testing

Leandro Gomes da Silva Leandro Gomes da Silva · World Congress 2025

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella · World Congress 2023

1:14 min

Evolution of distributed SQL database architectures

Wei Hu Wei Hu · World Congress 2024

2:37 min

Optimizing technical profiles for AI sourcing and recruitment

Mina Golesorkhi Mina Golesorkhi · World Congress 2026 Europe

56 sec

Performing local A/B testing across multiple AI agents

Julia Kasper · Coffee With Developers

Videos

See all

Related articles

See all