Freelancer profile translated to English.

Description

My career is guided by a fundamental conviction: technology, and in particular artificial intelligence, which I discovered at a pioneer in AI for HR functions back in 2014.

Standing at the intersection of AI, science, data, and technology, I now wish to contribute to innovative and value-generating projects.

My journey has allowed me to appreciate how much innovation, empathy, and scientific rigor are essential for developing structuring projects and sustainably transforming a business. I am resolutely determined to leverage my skills and experience to make a concrete and significant impact with 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 (5 months)
Leading the Data & AI foundation to provide reliable, scalable, and responsible data foundations for all analytical and artificial intelligence uses.
Designing and implementing a target data & AI architecture in a complex, multi-tool, and multi-domain environment, in collaboration with IT and data teams.
Structuring and industrializing strategic data assets necessary for AI use cases (features, certified datasets, data marts, training sets).
Defining and deploying common Data & AI standards: quality, traceability, security, metadata management, explainability, and model reproducibility.
Implementing end-to-end data lineage and model lineage, ensuring transparency, auditability, and regulatory compliance of data and AI pipelines.
Managing data quality foundations adapted to analytical and AI uses (completeness, freshness, consistency, data drift).
Designing and deploying a Data & AI management platform (cataloging, quality, governance, feature management, monitoring).
Implementing structuring Data & AI processes: ingestion, data certification, feature preparation, provisioning, evolution, and decommissioning.
Automating documentation, quality controls, and traceability to secure the scaling of data & AI uses.
Contributing to the definition and operationalization of responsible AI principles: explainability, robustness, bias control, and regulatory compliance.
Transforming heterogeneous data assets into industrialized and reusable foundations, accelerating the time-to-market for AI use cases.
Close collaboration 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)
Leading data and artificial intelligence products applied to pharmaceutical uses (R&D, clinical trials, manufacturing, supply chain, marketing, medical affairs).
Translating complex business problems into high-value data/AI use cases.
Awareness of responsible AI issues: explainability, bias, robustness, regulatory compliance.
Collaborating with business units to translate needs into data solutions.
Implementing and maintaining data products for business units.
Designing datasets and a Data Mart to feed a business intelligence and decision-making platform for the French supply chain.
Analyzing, validating, transforming, and optimizing critical data flows.
Defining governance rules, data quality standards, and mapping/reconciliation strategies between heterogeneous source systems.
OPEN LAKE TECHNOLOGY
DATA & AI FOUNDATION LEAD
TELECOMMUNICATIONS
February 2024 - July 2024 (5 months)
Paris, France
Leading the group's Data & AI foundation, supporting network, customer, finance, marketing, fraud, customer service, and operations uses.
Designing and evolving the target data & AI architecture in a complex telecommunications environment (networks, OSS/BSS, CRM, billing, IoT, real-time).
Structuring and industrializing critical data assets (network, customer, traffic, real-time events, repositories) for analytical and AI uses.
Implementing a Data & AI Foundation platform integrating batch & streaming ingestion, cataloging, quality, governance, and pipeline monitoring.
Defining and deploying transverse Data & AI standards: quality, freshness, availability, traceability, security, and compliance.
Implementing end-to-end data lineage and model lineage, ensuring auditability and understanding of data flows and AI models.
Managing data quality foundations adapted to telecommunications uses (high volume, real-time, multi-source, strict SLAs).
Designing and providing certified datasets and feature stores to accelerate the development and industrialization of AI models.
Implementing structuring Data & AI processes: ingestion, qualification, certification, provisioning, evolution, and decommissioning of assets.
Automating documentation, quality controls, and traceability to secure scaling.
Contributing to responsible AI: model explainability, bias control, robustness, and regulatory compliance (customer data, security, GDPR).
Transforming heterogeneous data assets (network, IT, digital) into industrialized and reusable data foundations.
Close collaboration with network, IT, data, cybersecurity, and business teams to align platforms, uses, and operational constraints.