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Permanent
Île-de-France
Saint-Ouen
Data
Full - Time
01-Apr-2026

Context 

Digital technology is increasingly at the heart of the L'Oréal group's strategy and its brands. Whether it's enhancing the point-of-sale experience, offering new services directly to consumers, or transforming the working methods of our researchers, the digitalization of L'Oréal's expertise is key to this transformation. The role of data science is increasingly growing in the daily work of our researchers, who rely on characterization, modeling, in silico prediction, data analysis and knowledge extraction from unstructured data to address today major cosmetics challenges, such as green formulation, a pillar of the L'Oréal for the Future program.


The Artificial Intelligence & Data Science team is in charge of defining and enacting the algorithmic strategy for R&I in order to support its digital transformation. Working with local teams in entities and hubs, this team structures, provides tools and methods, and tackles research topics on all strategical algorithm topics for L’Oréal R&I. From Deep learning to LLMs, from attention based to diffusion models, from Bayesian statistics to Design of experiments, this team oversees the development, industrialization and run of algorithms. 


By joining the AI&DS team, you will contribute to topics ranging from exploration to product-oriented with a specific focus on the construction of generative AI pipelines applied to the field of chemistry (knowledge recovery, formulation, …). You will be responsible for understanding and translating end-user needs into algorithmic constraints/specifications, enabling you to develop new methods (adapted from the literature or developed specifically for the task). You will also be responsible for the analysis and scientific validation of the results obtained. You will act as a technical expert during the technology transfer to the user facing products and ensure their successful integration. 


MISSIONS 

  • Participate in L’Oréal Research worldwide activities for innovative methods and applications.
  • Work along with Data Scientists worldwide to develop statistical analysis process, plans and determine appropriate statistical methodology for data analysis as part of the study protocol and design. 
  • Take ownership of data science topics.
  • Independently apply and implement basic and complex statistical technics to help translate data into information, support results interpretation. 
  • Conduct technological monitoring of evaluation and predictive formulation methods.
  • Understand and translate user needs into algorithmic specifications.
  • Design and implement algorithms that effectively meet these needs.
  • Handle data to support the development of these algorithms (needs specifications, preparation, preprocessing, etc.)
  • Define evaluation protocols, analyze the performance of the methods developed and quantify the impact on the end-user.
  • Ensure the intellectual property protection of our innovations and participate in the company's scientific influence (patents, publications in journals or conferences, etc.)
  • Document and present the work carried out to team members and management
  • Contribute to decision making, interpret statistical results in a clear and clean way to help project leaders make data driven decisions. 
  • Actively promote the use of data visualization and analytics field by leading a community of data analyst citizens. 
  • Maintain current and build up new external networks and introduce relevant technology to accelerate innovation.


REQUIRED SKILLS

Functional and technical skills:

Mandatory: Programming (Python, R, LangChain, Scikit-Learn, Keras, PyTorch, Tensor Flow, Numpy, Pandas, Docker, Git). Statistics (Mixed models, Bayesian analysis, computational statistics, numeric analysis, ), Machine Learning/Deep Learning (Transformers, Diffusion models, ViT, GANs).

Nice to Have: Design of experiment, Code Productization, Software Engineering & Design, Data Engineering.

Personal & Interpersonal Skills:

Mandatory: Excellent communication skills, with the ability to explain technical topics clearly to both technical and non-technical audiences. Ability to work autonomously and manage priorities, problem-solving ability, self-starter. Strong collaboration, influence and facilitation skills, particularly within a project-based environment.  Fluent English speaker.

Nice to have: knowledge of cosmetics and formulation

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