Freelancer profile translated to English.

Description

My career is guided by a fundamental belief: technology, and in particular artificial intelligence, must be used to serve human innovation and optimization. Standing at the crossroads of AI, science, data, and technology, I now wish to contribute to innovative and value-generating projects. My career has shown me how essential innovation, empathy, and scientific rigor are for building structuring projects and sustainably transforming a business. I am resolutely determined to leverage my skills and experience to make a concrete and significant impact for each client.

Industry field of expertise

Languages

French
Native or bilingual
English
Native or bilingual
Spanish
Fluent

Workplace preferences

Can work on-site

Paris (up to 20km)

Laboratoire pharmaceutique (confidentiel)
DATA MANAGER (Data & AI foundation Lead)
PHARMACEUTICALS INDUSTRY
January 2026 - Today (7 months)
Led the Data & AI foundation to provide reliable, scalable, and responsible data foundations for all analytical and artificial intelligence uses.
Designed and implemented a target data & AI architecture in a complex, multi-tool, and multi-domain environment, in conjunction with IT and data teams.
Structured and industrialized strategic data assets necessary for AI use cases (features, certified datasets, data marts, training sets).
Defined and deployed common Data & AI standards: quality, traceability, security, metadata management, model explainability, and reproducibility.
Implemented end-to-end data lineage and model lineage, ensuring transparency, auditability, and regulatory compliance of data and AI pipelines.
Managed data quality foundations adapted to analytical and AI uses (completeness, freshness, consistency, data drift).
Designed and deployed a Data & AI management platform (cataloging, quality, governance, feature management, monitoring).
Implemented structuring Data & AI processes: ingestion, data certification, feature preparation, provisioning, evolution, and decommissioning.
Automated documentation, quality controls, and traceability to secure the scaling of data & AI uses.
Contributed to the definition and operationalization of responsible AI principles: explainability, robustness, bias control, and regulatory compliance.
Transformed a heterogeneous data heritage into industrialized and reusable foundations, accelerating the time-to-market for AI use cases.
Collaborated closely with data scientists, data engineers, IT teams, and business units to align technical foundations, regulatory constraints, and business needs.
SANOFI
DATA PRODUCT MANAGER
September 2024 - September 2025 (1 year)
Managed data and artificial intelligence products applied to pharmaceutical uses (R&D, clinical trials, manufacturing, supply chain, marketing, medical affairs).
Translated complex business issues into high-value data/AI use cases.
Aware of responsible AI issues: explainability, bias, robustness, regulatory compliance.
Collaborated with business units to translate needs into data solutions.
Implemented and maintained data products for business units.
Designed datasets and a Data Mart to feed a business intelligence and decision support platform for the French supply chain.
Analyzed, validated, transformed, and optimized critical data flows.
Defined data governance and quality rules, and mapping and reconciliation strategies between heterogeneous source systems.
OPEN LAKE TECHNOLOGY
DATA & AI FOUNDATION LEAD
TELECOMMUNICATIONS
February 2024 - July 2024 (5 months)
Paris, France
Led the group's Data & AI foundation, supporting network, customer, finance, marketing, fraud, customer service, and operations uses.
Designed and evolved the target data & AI architecture in a complex telecom environment (networks, OSS/BSS, CRM, billing, IoT, real-time).
Structured and industrialized critical data assets (network data, customer data, traffic data, real-time events, repositories) for analytical and AI uses.
Implemented a Data & AI Foundation platform integrating batch & streaming ingestion, cataloging, quality, governance, and pipeline monitoring.
Defined and deployed cross-functional Data & AI standards: quality, freshness, availability, traceability, security, and compliance.
Implemented end-to-end data lineage and model lineage, ensuring auditability and understanding of data flows and AI models.
Managed data quality foundations adapted to telecom uses (high volume, real-time, multi-source, strict SLAs).
Designed and provided certified datasets and feature stores to accelerate the development and industrialization of AI models.
Implemented structuring Data & AI processes: ingestion, qualification, certification, provisioning, evolution, and decommissioning of assets.
Automated documentation, quality controls, and traceability to secure scaling.
Contributed to responsible AI: model explainability, bias control, robustness, and regulatory compliance (customer data, security, GDPR).
Transformed a heterogeneous data heritage (network, IT, digital) into industrialized and reusable data foundations.
Collaborated closely with network, IT, data, cybersecurity, and business teams to align platforms, uses, and operational constraints.