Pour un acteur de l'assurance
Contexte
This mission focuses on establishing a comprehensive framework for Unstructured Data Management to support data and AI-driven initiatives. It aims to define standards, rules, and frameworks that guarantee data reliability and reusability, facilitating scalable data and AI solutions through collaboration with relevant stakeholders. The activity includes piloting innovative approaches, consolidating learnings, and ensuring alignment with broader data strategies.
Missions
Development of the methodological foundation for Unstructured Data Management aligned with industry best practices.
Definition and documentation of standards, rules, and frameworks to ensure data quality, consistency, and reusability.
Coordination with internal stakeholders to gather feedback and ensure alignment with strategic objectives.
Pilot testing of innovative Unstructured Data Frameworks and integration of insights into operational practices.
Evaluation of technology vendors, benchmarking solutions, and recommending suitable tools and platforms.
Assessment of document processing techniques (OCR, NLP, VLM), metadata management, ontologies, and vector database solutions.
Supporting transformation initiatives related to data utilization for AI and analytical purposes.
Informations complémentaires
Service Deliverables (but not limited to)
A comprehensive methodological framework for Unstructured Data Management.
Documented standards, policies, and rules for data quality, metadata, and data architecture.
Reports on pilot projects, including lessons learned and best practices.
Vendor evaluation reports and benchmarking analyses.
Technical documentation on document processing techniques and data transformation methods.
Recommendations for tools, platforms, and implementation plans aligned with operational needs.
Profil recherché
Required Expertise
Extensive experience in data management disciplines such as Data Governance, Metadata, Data Quality, Data Architecture, and Data Modeling.
Proven track record in deploying operational data management activities within complex environments.
Strong knowledge of document processing technologies (OCR, NLP, VLM) and metadata/ontology management.
Deep understanding of unstructured data utilization for data and AI projects, including transformation initiatives.
Familiarity with vendor evaluation, benchmarking, and solution assessment methodologies.
Fluency in English, both spoken and written.
Service Qualifications
Demonstrated expertise in establishing data frameworks and standards within data-driven or AI-focused projects.
Ability to communicate complex technical concepts clearly to diverse stakeholders.
Analytical and synthesis skills to interpret data management challenges and develop practical solutions.
Proven capability to collaborate effectively across technical and business teams.
Experience guiding innovation pilots and consolidating insights into scalable frameworks.