Senior Data Scientist NLP/GenAI - Catalog

Mirakl - Labs · Bordeaux, France

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About Mirakl:

Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy.

Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus).

With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.

For more information: www.mirakl.com.

Mirakl in Numbers:

  • 🗓️ Founded in 2012 | Member of French Tech Next40
  • 👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo
  • 🇫🇷 350+ Mirakl Tech teams members mainly based in France
  • ⚙️ 5 Saas Solutions

Our Values:

Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique.

Our 5 values guide how we collaborate:

  • 💡 Work Hard Together: Teamwork and collaboration are the foundation of our success
  • 🏆 Get Things Done:  We prioritize action and efficiency for impactful results
  • 🚀 Go Above & Beyond:  We tackle challenges proactively and always aim for excellence
  • 🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture
  • 🤝 Satisfy & Empower Clients: We're committed to our clients' success

The Team You'll Join

You'll be part of our Catalog Data Science team led by Arthur Delaitre and Adrien Morvan.
As part of our broader Data team (60+ people), you'll be prototyping, iterating, and shipping algorithms to production that directly impact marketplace catalog challenges—from NLP to large-scale Generative AI with custom LLMs.
Our opportunity can be located in Paris or Bordeaux and requires 4 days onsite per week, 1 day remote.
 
Meet Arthur Delaitre, Data Science Manager for the team:
 
 

Your Impact

What You'll Bring to the Role

Experience:
Skills:

Tech Stack

Core ML/AI:
LLM-specific:
Data infrastructure:

Our Hiring Process

We warmly encourage you to apply to any of our roles, even if you think you're not an exact match.
 
Hiring steps:
  1. A 45-minute phone call with one of our Tech recruiters to discuss your background, expectations, and the role
  2. A 45-minute technical call with someone from the Data Science team to dive into concrete aspects of your expertise and how it fits our projects
  3. A take-home assignment to demonstrate your technical skills
  4. A 1:30 technical debrief and discussion with the Data Science Team managers
  5. 2x45mn STAR interviews with future Mirakl colleagues to discuss our values and culture

We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you’re ready to join a global leader powering digital transformation for 450+ of the world’s most innovative retailers and B2B organizations.

As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French. 

We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews.

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