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Stage 2027 AI/ML Engineer 100% R&D - Tabular foundation models

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EMP:Technology
Paris
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Latent Reasoning for Tabular Foundation Models: Performance Enhancement and Interpretability      Ekimetrics is the European leader in data science, with over 500 data scientists and 1,000+ projects since 2006.

With offices in Paris, London, New York, and Hong Kong, we conduct projects in over 50 countries across various sectors, including financial services, retail, telecom, healthcare, and more.

  Our mission is to help companies audit their data opportunities, enhance their analytical capital, and deploy actionable solutions that maximize their marketing and operational performance while reinvigorating business models.

  Our absolute focus is on delivering short-term gains while ensuring the long-term development of our clients' data capital.

We are committed to offering the most advanced data science approaches and building ethical, sustainable AI practices.

  Key Figures  20 years of experience in data science  500+ data scientists, all consultants  5 offices in Paris, London, New York, Hong Kong, and Shanghai  350+ clients (CAC40, Fortune500)  $1M+ in profit generated for our clients since 2006  1,000+ data science projects  Within Ekimetrics, the Innovation Department works on AI research topics in collaboration with our industrial and academic partners.

The department comprises several PhD experts in generative AI, deep learning, computer vision, time series, explainability, and causality.

Each expert leads teams tasked with studying and building state-of-the-art methods and adapting them to specific business problems, developing new methodologies or algorithms to address identified challenges, and ensuring a seamless handover for integration within Ekimetrics' industrial ecosystem.

  A central focus of the Innovation Department is closing the gap between cutting-edge AI agents and the day-to-day reality of delivering data science at scale.

The department is investing in agentic systems that accelerate the data science lifecycle while keeping data scientists.

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