Head of AI Center of Excellence

The Head of AI Center of Excellence is responsible for defining, industrializing, and scaling AI capabilities across the enterprise. This role transversal support of the AI foundations and AI deliveries requiring AI skills.

The AI CoE acts as a delivery accelerator: enabling and supporting business teams to build, deploy, and scale AI solutions efficiently

The role covers the full AI lifecycle supporting the transversal deliveries of AI Office, this includes data, model development, deployment (MLOps/LLMOps), Responsible AI, and value measurement, with a strong focus on industrialization, reuse, and business impact.

Key duties and responsibilities

Approach

The Head of AI Center of Excellence is responsible for managing the resources to support the different AI strategic initiatives driven by AI flagships.

He/She maintains a high level of skills to support industrialization of AI and maintenance of AI models used in different product or service features

• Operate under the Agile Framework and is accountable for the quality of the work delivers and ensuring that Core Data Scientist and Machine Learning Engineers works respect the AI delivery operating model (documentation process, proper usage of tools, state of the art standards, SDLC, etc.)

• Manage the external resources capacity under the budget envelope provided

• Allocate effectively resources within squads & projects

• Ensure the application of best practices and AI delivery framework in deliveries supported by the AI CoE

Skills

• Maintain a high level of skills in adequation with Data & AI platform (Fast learning)

• Experience in Industrialization of AI solutions (AI flow, CI/CD, SDLC)

• Machine Learning Engineering and Data Science (Model packaging, MLOps)

• Cloud usage (K8s, PostgreSQL, storage, on Azure is a plus)

• Python (OOP, FastAPI – CRUD)

Required experience & competencies

• ~7+ years’ experience in data science with solid programming capabilities and knowledge of supervised and unsupervised machine learning techniques
• Advanced knowledge in/ Specialized in a core DS area : Image Processing, NLP, Survival Analysis, …
• Develops and promotes coding best practices across the community
• Management of teams or squads / experience in resource allocation

Soft skills

• Can orchestrate resource planning
• Can manage AI experts 
• Can perform a code peer review and advise on enhancements
• Supports other data scientists and transfers knowledge on modelling topics
• Can play the role of technical lead or product owner on highly technical projects (prioritise squad efforts, ensure delivery of a project, etc.)
• Can conduct the delivery of the project and its full documentation (reports, slides for clients, management, peers or conferences)

• Can evolve in international context 

  Required Education 

• Master’s degree (Ph. D. is a plus) in Science, Technology, Engineering, Mathematics, Computer Science, Actuarial or similar quantitative field
• Bachelor’s degree plus ASA or similar work experience is accepted in place of a relevant Master’s degree.