Unleash Your Potential at L’Oréal’s Beauty Tech!

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.

Today, L’Oréal includes more than 2,000 tech positions and is constantly growing. 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, Applications and Infrastructure.

We are searching for a highly motivated and data- driven Omnichannel Project Manager to play a pivotal role in optimizing our understanding of L’Oréal omnichannel sellout performances in the market. In this role, you will be a key player in consolidating, standardizing, and analyzing omnichannel sell out data from various sources to provide actionable insights that drive business decisions at global level. This project will be driven by leveraging the group Beauty Market Referential to establish common standards and guidelines for sell-out data management across the organization.

Responsibilities:

• Project Leadership: Lead the design, implementation, and ongoing management pillars aimed at centralizing and harmonizing omnichannel sell-out data from diverse retail partners and internal countries and zones practices, ensuring alignment with the Group Beauty Market Referential.
• Stakeholder Management : Collaborate closely with cross-functional teams, including CMI and Sell Out Data teams at group and zone levels, along with IT global teams, to understand their data needs and ensure the project aligns with overall business objectives and adheres to established standards.
• Process Improvement: Analyze and assess existing omnichannel sell-out data collection and reporting processes, plan proper frame for project business perimeters target application and standardization in accordance with the Group Beauty Market Referential. Develop and implement procedures to enhance data accuracy, completeness, and timeliness.
• Data Integration : Manage the consolidation of omnichannel sell-out data from various sources, including panels, sell out estimations, B2B data, e-commerce data, ensuring data conformity with our group referential and the targeted business perimeters. The project industrialization will be done under the Agile methodology within the IT group umbrella. This may involve working as well with external vendors and internal IT resources to establish efficient data pipelines.
• Data Quality Assurance : Implement data quality control measures and validation processes to ensure the accuracy and reliability of consolidated sell-out data, adhering to the guidelines, together with Sell Out data teams guidelines.
• Data Analysis & Reporting : Generate reports and visualizations to communicate findings to key stakeholders and support data-driven decision-making, utilizing the business needs as a framework.

• Master’s Degree in Business Administration, Information Technology, Statistics, or a related field.
• Proven experience (5+ years) in project management, within a data-centric environment.
• Strong understanding of retail sales and distribution channels, with a focus on panels data.
• Expertise in data analysis techniques and tools, with the ability to manipulate and interpret large datasets.
• Experience with data visualization software and techniques to effectively communicate findings.
• Exceptional communication and interpersonal skills, with the ability to clearly explain complex data concepts to both technical and non-technical audiences.

• Experience working with sell-out data within the beauty or consumer goods industry.
• Familiarity with reporting consolidation and data governance principles.
• Knowledge of data integration tools and techniques (e.g., SQL).