Data Scientist AI R&D

If you’ve worn a pair of glasses, we’ve already met.

We are a global leader in the design, manufacture, and distribution of ophthalmic lenses, frames, and sunglasses. We offer our industry stakeholders in over 150 countries access to a global platform of high-quality vision care products (such as the Essilor brand, with Varilux, Crizal, Eyezen, Stellest and Transitions), iconic brands that consumers love (such as Ray-Ban, Oakley, Persol, Oliver Peoples, Vogue Eyewear and Costa), as well as a network that offers consumers high-quality vision care and best-in-class shopping experiences (such as Sunglass Hut, LensCrafters, Salmoiraghi & Viganò and the GrandVision network), and leading e-commerce platforms.

Join our global community of over 190,000 dedicated employees around the world in driving the transformation of the eyewear and eyecare industry.

Discover more by following us on LinkedIn! 

Your #FutureInSight with EssilorLuxottica

Are you willing to pioneer new frontiers, foster inclusivity and collaboration, embrace agility, ignite passion, and make a positive impact on the world? Join us in redefining the boundaries of what’s possible.

Your role:

To lead AI research initiatives for medical imaging applications, focusing on predictive analytics, disease progression modeling, and statistical validation. This role ensures AI models remain at the forefront of healthcare AI advancements and align with scalable research and delivery methodologies.

Main responsibilities::

·       Identify, explore, and validate new AI methodologies to enhance medical imaging, diagnostics, and predictive analytics using advanced data analytics tools.

·       Research and develop novel deep learning architectures tailored for medical imaging challenges, improving model performance, explainability, and real-world application.

·       Investigate and propose AI-driven solutions for improving disease diagnosis and risk assessment, leveraging responsible AI frameworks.

·       Go beyond traditional deep learning techniques by integrating multi-modal learning, self-supervised learning, and federated learning to handle limited labeled medical datasets.

·       Optimize and test different AI model architectures (CNNs, Vision Transformers, GANs, Graph Neural Networks) for efficiency, robustness, and clinical applicability.

·       Continuously assess AI biases, fairness, and ethical risks, and propose new techniques to mitigate biases in AI-driven healthcare solutions.

·       Develop AI model validation frameworks that ensure regulatory compliance and reliability in real-world clinical settings.

·       Collaborate with engineering and medical teams to translate cutting-edge research into scalable, deployable AI solutions.

·       Contribute to patents, peer-reviewed publications, and research grants, advancing the organization’s position in AI-driven medical research.

·       Lead problem-solving initiatives, pushing the boundaries of AI applications in ophthalmology, diagnostics, and healthcare analytics.

Main requirements:

·       Master’s or Ph.D. in Data Science, Biostatistics, or a related field.

·       Experience with Python, R, SQL, and Azure Data Factory for ETL workflows.

·       Strong understanding of statistical modeling, AI fairness, and bias mitigation in AI-driven healthcare solutions.

·       Expertise in interpretable AI (XAI) methodologies and Azure AI governance frameworks.

·       Familiarity with medical imaging datasets (DICOM, PACS) and Azure cloud computing.

·       Knowledge of Azure Databricks and encryption/decryption techniques.

Recruiting process

If you are selected, you will be contacted by HR Department to guide you through the specific steps for your application.​

Our Diversity, Equity and Inclusion commitment​

We are committed to creating an inclusive environment for all employees. We celebrate diversity and provide equal opportunities to all, regardless of race, gender, ethnicity, religion, disability, sexual orientation, or any other characteristic that makes us unique.