Data Scientist

• Manage, coach and develop a growing team of Data Product Owners
• Set objectives, ways of working and expectations, and coordinate team capacity and workload
• Lead the end-to-end lifecycle of Data Products from discovery and definition through delivery, adoption and lifecycle management
• Shape and communicate Data Product vision and strategy with business domains
• Guide a portfolio spanning data tables, transformations, dashboards, analytical services and ML/AI products
• Support Data Product Owners in gathering, qualifying and structuring data product requests
• Assess feasibility, value, urgency and risk of data product opportunities
• Translate business needs into product briefs, business cases, requirements, MVPs and acceptance criteria
• Establish product management practices, standards and governance for design, documentation, quality, testing, releases and lifecycle management
• Coordinate Data Product Owners with Data Science and Data Engineering teams, managing dependencies and resolving risks and blockers
• Define and track product success measures, adoption, quality and user satisfaction
• Guide dashboard portfolio standards, usage expectations and lifecycle management
• Oversee product management for ML and AI products, including business objectives, model limitations, deployment requirements and adoption
• Direct Product Analytics Enablement & Instrumentation, including Amplitude adoption, community animation, user training, support and tagging-plan management
• Ensure product analytics data is consistently defined, collected, validated and available in relevant systems
• Promote data product adoption and a data-driven culture
• Represent the Data Product function with senior stakeholders and business domains
• Identify and champion innovative data solutions and best practices that create measurable business value

Head of Data Product shaping data products for Betclic’s online gaming platform

Head of Data Product

Head of Data Product leading Data Product Owners and data product adoption. Shaping analytics, ML and AI products for Betclic’s online gaming platform.

• Ensure the documentation of data and metadata within the CMC domain
• Perform data quality checks and ensure Data Integrity
• Prepare, cleanse, and standardize datasets
• Contribute to data integration and management on Google Cloud Platform (GCP)
• Manage data access and contribute to migration and archiving activities
• Implement and monitor automated data quality controls
• Coordinate interactions with external data providers
• Produce and maintain reporting related to Data activities
• Contribute to the continuous improvement of data management processes
• Collaborate with business, IT, and Data teams to ensure data availability and reliability

Data Manager CMC gérant la qualité des données pharmaceutiques chez Excelya, CRO européenne

Data Manager – CMC

Data Manager CMC gérant les données Chemistry, Manufacturing & Control chez Excelya, CRO de santé. Assurant qualité, intégration cloud et fiabilité des données pharmaceutiques.

• Lead data management for complex, global clinical trials from study setup to database lock
• Serve as the main client contact for all data management deliverables
• Oversee SAE, PK, and external data reconciliation and database deployment
• Manage timelines, budgets, and resource allocation to meet customer expectations
• Mentor junior data management staff and promote best practices
• Drive process improvements and ensure regulatory and SOP compliance

Lead Data Manager overseeing clinical trials at a global healthcare company

Data Team Lead

Lead Data Manager overseeing end-to-end data management delivery for global clinical trials. Responsible for quality, accuracy, and compliance while mentoring teams and driving process improvements.

• Lead a multidisciplinary Data Science team and contribute to the development of innovative machine learning solutions embedded in medical devices.
• Combine scientific expertise, technical leadership and people management to drive the development of next-generation AI algorithms.
• Define and drive the Data Science roadmap in alignment with product and business priorities.
• Lead the design, development and validation of Machine Learning and Deep Learning algorithms.
• Ensure scientific excellence and promote best practices in AI research and development.
• Stay up to date with the latest advances in AI and identify opportunities to integrate new technologies into products.
• Support the definition of data strategies and contribute to the continuous improvement of data collection pipelines.
• Lead, mentor and grow a team of Data Scientists, Data Engineers and PhD researchers.
• Foster a collaborative, innovative and high-performance culture.
• Coach team members in both technical and professional development.
• Collaborate closely with Software Engineering, Clinical, Regulatory and Product teams throughout the product lifecycle.
• Ensure production-ready, maintainable and high-quality code.
• Participate in the preparation of technical documentation required for regulatory submissions.
• Represent Volta Medical at scientific conferences and technical events.
• Contribute to publications, patents and collaborations with academic partners.

Lead Data Scientist at Volta Medical developing AI solutions for electrophysiology

Lead Data Scientist

Lead Data Scientist developing innovative AI solutions for medical devices in electrophysiology labs. Managing a multidisciplinary team and driving AI technology development in the healthcare sector.

• Développer et optimiser des modèles de Machine Learning et de Deep Learning pour l’analyse et la classification de données complexes
• Concevoir des pipelines de traitement de données et assurer leur déploiement dans des environnements locaux et cloud
• Collecter, préparer et exploiter des données afin de produire des analyses fiables et exploitables
• Collaborer avec des équipes scientifiques et techniques pour répondre à des problématiques innovantes à l’intersection de l’IA et des neurosciences
• Participer à la veille technologique, à la valorisation des travaux de recherche et au développement de solutions réutilisables

Data Scientist in AI and Neuroscience at Capgemini Engineering

Data Scientist – IA, Neurosciences

Data Scientist focusing on Machine Learning in AI and Neurosciences at Capgemini Engineering. Responsibilities include developing models and collaborating with scientific teams.

• Concevoir, développer et améliorer des modèles prédictifs à forte valeur (e.g., scoring, Next Best Offer, segmentation clients, etc.)
• Exploiter et croiser des données multi-sources (e.g., CRM, parcours digitaux, etc.)
• Industrialiser les modèles et assurer leur mise en production dans des environnements robustes
• Garantir la performance et la pérennité des modèles déployés
• Analyser les parcours clients et les tunnels de conversion
• Mettre en place des dispositifs d’évaluation des modèles (e.g., A/B testing, uplift, valeur client, etc.)
• Accompagner les métiers dans l’interprétation des résultats et la mise en œuvre d’actions concrètes dans une logique ROI
• Définir et promouvoir les bonnes pratiques Data Science et MLOps

Data Scientist designing AI models for e-business performance optimization at Crédit Agricole.

Data Scientist, Confirmé

Data Scientist designing and industrializing AI models for optimizing e-business performance at Crédit Agricole. Collaborating with teams to enhance customer insights and marketing effectiveness.

• Drive and maintain the data catalog to ensure reliable, up-to-date documentation
• Identify and inventory the company's strategic data
• Define and maintain business, functional, and technical metadata
• Map data flows and maintain data lineage
• Document Data Products and contribute to the dissemination of governance standards
• Define and implement data quality rules
• Build data quality monitoring metrics and manage their evolution
• Develop continuous improvement plans for data quality
• Support data compliance with regulatory requirements and internal policies
• Participate in data projects to integrate governance requirements from the design phase
• Lead workshops with various stakeholders
• Produce governance reports and Data maturity indicators
• Ensure knowledge transfer and promote a data-driven culture within teams

Data Manager managing data governance projects for large clients in Nantes

Data Manager

Data Manager managing governance and quality of data for OPEN's clients in Nantes. Collaborating within a cross-functional team to ensure data management excellence.

• Industrialization of the integration system: Lead the full migration to the Seyna application, eliminate ad-hoc manual steps, and ensure end-to-end operational scalability.
• Quality & speed standards: Define and maintain standards for bordereaux integration (data correction, writing acceptance tests), explicitly arbitrating trade-offs between quality and deadlines.
• Team management: Structure and lead a team of 3 Data Integration Managers — run operational rituals, allocate scopes, coach and upskill team members.
• Relationship with Tech: Manage the relationship with Tech teams to prioritize Seyna application enhancements and prevent reverting to ad-hoc solutions.
• Business continuity: Ensure continuity across each portfolio by enforcing documentation as a non-negotiable standard and anticipating critical dependencies.
• Service relationships: Structure the relationship with consumer teams (Actuarial, Accounting, Portfolio Owners, Client Performance) to align data with real business needs.
• Cross-functional projects: Lead cross-functional initiatives with other teams (CSM, Legal, Tech...) and continuously arbitrate between speed, quality, workload and business expectations in a high-pressure operational environment!

Manager leading data integration team at an insurtech company in Paris

Manager – Data Integration

Manager overseeing data integration and quality assurance in a hybrid role at Seyna in Paris. Leading team to enhance operational scalability, compliance, and customer satisfaction.

• Lead, manage, and motivate an on-site team of annotators working on technical annotation, owning daily team coordination and overall performance
• Run daily operations: task progress and completion tracking, shift coordination, and follow-through so that assigned work is finished and nothing falls through the gaps
• Own annotation quality end-to-end: make sure the standard operating procedures and guidelines are followed, run calibration sessions and targeted refresher trainings, monitor acceptance and rejection rates against targets, and lead root-cause analysis and corrective actions on recurring errors
• Act as the operational point of contact with the client's quality and engineering teams: align on guidelines and specifications, manage the rework loop, and escalate ambiguities or contradictions with clear, documented evidence
• Design, implement and maintain daily quality and productivity tracking and reporting, and provide clear, honest status to the client and DataForce’s program management team
• Interview, test, onboard, train, coach, and develop annotators, and manage individual performance and feedback
• Keep the team aligned as tools, guidelines, and the rating scale evolve, translating changes into clear and consistent instructions across shifts
• Ensure full adherence to confidentiality and data handling requirements
• Coordinate internally with DataForce’s operations and account management team to continuously improve our client services and experience

Team Lead managing data annotators for AI training data at DataForce

Team Lead – AI Data Annotation

Team Lead managing data annotators for AI training data in Paris. Leading team performance, ensuring quality and coordinating with clients for a fast-evolving AI program.

• Le Data Scientist conçoit et met en œuvre des modèles analytiques et d’intelligence artificielle
• Explorer et analyser des jeux de données complexes
• Identifier des patterns, corrélations et leviers de performance
• Produire des analyses statistiques pour extraction d’insights
• Concevoir des modèles de Machine Learning et Deep Learning
• Adapter les modèles aux cas d’usage métier
• Mettre en production les modèles
• Assurer le monitoring et le maintien des performances
• Travailler avec les métiers pour identifier les cas d’usage
• Traduire les besoins métier en modèles analytiques
• Concevoir des cas d’usage sur IA générative
• Proposer des solutions innovantes
• Collecter, nettoyer et préparer les données

Data Scientist designing and implementing analytical models at Alenium

Data Scientist designing and implementing analytical and AI models for organizational transformation at Alenium. Collaborating on complex data projects to produce actionable insights.

• Caractériser et proposer une rationalisation des bases de données Produits utilisés par l’équipe OSM et au-delà
• Soutenir toutes les mises en place de Key Value Indicators/Attributes, Key Performance Indicators sur les initiatives de développement produit stratégiques
• Soutenir les réflexions et la stratégie des Opérations sur la continuité numérique
• Être un acteur du changement de l’équipe OSM dans son usage quotidien de la data et du numérique

Ingénieur Product Data Manager at Thales in Cannes, transforming data management in space.

Ingénieur Product Data Manager

Ingénieur Product Data Manager at Thales, focusing on data management in satellite systems. Collaborating with cross-functional teams for product development and operational strategy.

• Lead structured data operations end-to-end, ensuring timely and compliant submissions to Health Authorities worldwide.
• Manage and develop a team of structured data specialists to meet all compliance requirements and quality standards.
• Drive the global implementation of IDMP standards and monitor changes to regulatory data requirements.
• Represent Sanofi in working groups with Health Authorities and industry partners to shape regulatory innovation.
• Oversee data quality control and track Key Performance Indicators (KPIs) to ensure on-time submissions.
• Set up and monitor service agreements with vendors and contractors to ensure operational excellence and timely delivery.
• Provide expertise during audits and support inspection processes with required documentation and responses.
• Work with stakeholders to continuously improve structured data processes and build team expertise.

Submission Lead for Structured Data managing global regulatory submissions at Sanofi

Submission Lead – Structured Data

Submission Lead for Structured Data in Global Submission Management at Sanofi. Leading regulatory data standards implementation for timely, compliant submissions to Health Authorities worldwide.

• Operate at the intersection of data engineering, clinical science, and partner collaboration
• Participate directly in technical conversations with external partners (hospitals, research institutions, CROs/CMOs)
• Translate ambiguous source data into harmonized, AI-ready assets
• Map and align diverse clinical data to industry-standard biomedical ontologies with an emphasis on clinical oncology and immunology data
• Design, build, and maintain data dictionaries, schemas, and metadata models
• Establish, automate, and enforce data quality control (QC) and validation frameworks
• Write production-grade Python code to automate data cleaning and harmonization tasks
• Understand how clinical data is generated in real-world settings
• Actively audit data to find missing variables, anomalies, and hidden biases
• Recognize important data in clinical trials related to oncology/immunology

Clinical Data Manager bridging clinical data and AI models for Bioptimus

Senior Clinical Data Manager

Clinical Data Manager coordinating data engineering and clinical science to standardize data for AI models. Join Bioptimus in reshaping biomedicine with AI-driven insights.

• Build from scratch and lead the Data Labeling team (hiring, coaching, and performance management)
• Define annotation guidelines, quality standards, and evaluation frameworks
• Develop quality assurance processes, calibration sessions, and auditing systems
• Partner with AI researchers and engineers to translate research objectives into labeling workflows
• Prioritise labeling projects based on business and research needs
• Monitor operational metrics including quality, consistency, throughput, and cost
• Improve annotation tooling, automation, and workflow efficiency
• Lead complex AI evaluation projects, including safety, preference ranking, RLHF, policy evaluation, and benchmark creation
• Analyse disagreement patterns and edge cases to improve guidelines and model performance
• Manage vendor relationships and ensure consistent quality across distributed teams
• Build reporting dashboards and communicate operational insights to leadership
• Foster a culture of continuous improvement, accountability, and operational excellence

Head of Data Labeling leading AI evaluation and data annotation team at AI Safety company

Head of Data Labeling

Head of Data Labeling overseeing data annotation and AI evaluation projects for an AI Safety company. Leading a team in defining standards and improving workflows and quality assurance processes.

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