Senior Data Scientist, Tech Accelerator Solutions

For more than a century, L'Oréal has devoted itself solely to one business: Beauty. Present in 150 countries across five continents and with €42 billion consolidated sales, L'Oréal is the global industry leader. With 37 global beauty brands across four divisions, L'Oréal offers beauty for each covering all beauty categories and catering to all beauty desires. With the acquisition of the Australian brand Aēsop in 2023, the Group continues to expand its portfolio through targeted acquisitions as part of its drive to create the future of beauty. Today, L'Oréal includes more than 2,000 tech positions and is constantly growing. Beauty Tech is changing the game and leading the shift towards new consumer realities and a digital disruption. Championing Beauty Tech, we invent the beauty of the future while becoming the company of the future. Beauty Tech is how we know our consumers intimately, augmenting their beauty journeys with unparalleled diverse and sustainable experiences. Beauty Tech equips the Group with the key assets it needs to conquer this new world, where Tech has become strategic. With this ambition, L'Oréal continues to recruit diverse, innovative, skilled and passionate minds in different tech domains such as Data, Digital, Cloud, Cyber Security, IT Architecture, DevOps, Product Design, Applications and Infrastructure. YOUR FUTURE TEAM L'Oréal is in a period of fast growth in digital transformation. To accelerate our ambition to be the global leader in Beauty Tech, we launched Tech Accelerator, a multidisciplinary venture studio composed of top talents from all types of backgrounds. With 4 hubs in Paris, New York, Shanghai and Singapore, our Tech Accelerator teams blend state-of-the-art technologies with product design to solve complex and strategic problems at scale for L'Oréal Groupe's long-term business ambition. Our tools are based on more than 120 TB of both structured and unstructured data. We create beautiful, reliable, high-quality tools for our colleagues. To do so, we don't only work together with Full Stack Software Engineers, DevOps, Product Owners and Product Managers, but also with UX/UI Designers and Business stakeholders. Our Paris team consists of 15 people, 4 of which compose the internal Data Science team. The team currently works on 3 high-stake products and on a few smaller initiatives. We build solutions with algorithms ranging from classic Machine Learning to LLMs, VLMs and Multi-Modal GenAI. Our infrastructure is mostly based on GCP (incl. Vertex AI) and Azure. On top of the regular work activities, we have a Weekly Data Science team meet, where we share perspectives and imaginations on the future of Data Science and Tech. Our team also participates in various external Data Science and Tech events, including VIVATECH in Paris, ICML in Vienna and others PyCon/PyData in Berlin. What a day in the team looks like: Each day in our team is different, thus you won't be bored. Among other things, this is what you will do: Drive innovation by designing and deploying cutting-edge Machine Learning and GenAI solutions that transform business operations Unlock strategic value from complex data, delivering actionable insights that influence high-impact decisions Lead and manage end-to-end data science projects, from development and integration of predictive models into products to ensuring seamless adoption, timely delivery, and measurable business results Communicate technical concepts and project outcomes clearly to both technical and business stakeholders Stay up to date with the latest industry trends, tools, and best practices in data science and analytics and participate to internal sharing sessions THIS IS WHAT YOU WILL NEED TO SUCCEED! First and foremost, we love people who are curious, collaborative, eager to have an impact, proactive and who value innovation, autonomy, and team spirit. Secondly, in this specific position, it will be important for you to have: Master's degree in a quantitative field (e.g., Statistics, Mathematics, Data Science) or a Bachelor's degree with 8+ years of relevant professional experience. 5+ years in a Data Scientist or similar role, encompassing data extraction, analysis, statistical modeling, and effective communication. Preferably, this includes experience as a leader and mentor within a Data Science team. Python, SQL, Git, Deep Learning, Statistical Modeling, Algorithms (incl. Machine Learning), NLP Algorithms (preferably), application / fine-tuning / development of LLM / Gen AI solutions (preferably) Ability to clarify and simplify technical concepts, experience of direct work Business Stakeholders, problem-solving, agile project management English B2+ level; French is a plus, but optional LET US GIVE YOU 6 OTHER REASONS TO JOIN US! Joining L'Oréal means joining a company that: Invests in Tech and positions its Tech teams at the heart of its digital transformation strategy. Allows its employees to have a real impact, to test their ideas, to innovate and to build our future. Offers a Hybrid Work Policy: 3 Days in the Office, 2 Days Work from Home (Work from home is permitted for a maximum of two Fridays per month) Provides many benefits: VIP staff shop offering our products at a preferential rate, a company restaurant & gym, 60% reimbursement of transportation subscription, a work council offering numerous employee discounts (social & cultural activities, holiday vouchers etc.) Delivers a powerful and innovative HR policy: dynamic mobility policy, significant investment in employee training, regular re-evaluation of remuneration, numerous innovative HR measures: Time Savings Account, paternity leave, Citizen Day, etc. Is an Equal Opportunity Employer and takes pride in a diverse environment. We would love to find out more about you as a candidate and we do not discriminate in recruitment, hiring, training, promotion, or other employment practices. The beauty we find in our differences gives us the freedom to go beyond. That's the beauty of L'Oréal.

L'Oréal, the global beauty leader, is a French personal care company that develops and sells beauty and hair products.