À propos de Sabine
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Expériences
- SERVIERData governance & transition leadINDUSTRIE PHARMACEUTIQUEavril 2025 - Aujourd'hui (1 an et 2 mois)Gif-sur-Yvette, FranceObjective: structure and deploy Data management foundations within a complex, siloed and regulated CMC organization.•Deployment of data management & governance strategy for the CMC domain: Pharmaceutical Industry, CMC Domain (500+ people, multi-site, regulated environment), coaching of the CMC data lead and presentations of data management roadmap to CMC Executive Committee.•Structuration of the data governance operating model: Data owners network, roles & responsibilities applied to CMC, ecosystem shaping, implementation of data domains and cross-site ways of working in a highly siloed context•Definition and initiation of MDM strategy: conceptual framework, roadmap and integration with IT ecosystem•Data integrity & risk framework: data criticality assessment, risk-based prioritization of processes, and structuration of processes & data documentation to support quality•Business workshops: definition of processes, centralization of data needs, mapping of data flows and definition of metadata framework•Adoption & data culture: extensive communication initiatives to drive data governance adoption across the CMC organization; educational sessions explaining Data Management principles and launching of a structured internal newsletter to increase visibility, engagement, and alignment
- Kraft Heinz - NL (European Holding B.V.)Data managerAGROALIMENTAIREseptembre 2024 - Aujourd'hui (1 an et 9 mois)Nimègue, Pays-BasObjective: comprehensive audit to identify data issues and understand how data is currently used to pinpoint areas for improvement.•Assessment of alignment between business needs and available data: identification of gaps and definition of recommendations tailored to the client priorities and the different stakeholders.•65 Interviews (worldwide, various functions): moderation guide, moderation, online survey, to evaluate data use, accessibility, expectations and data quality perception across the organization.•Data mapping framework: metadata accessibility, business context, end users, definition of data set and format.•Recommendations: data governance, data visualization, data storage, roadmap for next steps and definition of KPIs for future monitoring
- L'Oréal SA - L'Oréal FranceDATA MANAGERMODE & COSMÉTIQUESnovembre 2023 - juillet 2024 (8 mois)Paris, France•Data analyst: understanding business cases and end users’ expectations through in-depth collective and individual interviews, refining market segmentation, incorporating additional data fields to support deep dive analysis, collaborating with development teams to deploy dashboards.•Data quality: audit, cleaning, process implementation, follow-up with panel changes, close collaboration with external provider to establish data quality standard.•Data product owner: link between IT teams and end-users to ensure the accuracy and integrity of datafiles, ensuring the ingestion of data into the datalake, priorizing datafile migration to a new datalake and streamlining the process.•Data governance: centralizing data management and improving data governance practices, developing and redefining RACI matrices and processes.
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Formations
- Diplôme d'ingénieur, Sciences des alimentsAgroParisTech - Institut des sciences et industries du vivant et de l'environnement2012Diplôme d'ingénieur, Sciences des aliments
- Research Doctorate, Sciences cognitivesUniversité Claude Bernard Lyon 12016Research Doctorate, Sciences cognitives