Data Scientist Expert
Role details
Job location
Tech stack
Job description
As an AI Engineer expert, your main objective is to participate the development, implementation, and optimization of advanced AI solutions that support AXA Group's strategic goals, with hands-on activities when required. You will participate cross-functional topics, develop best practices in AI engineering across entities, and drive innovation to enhance customer experience, operational efficiency, and risk management. Additionally, you will collaborate with stakeholders to identify business needs, translate them into technical requirements, and ensure the successful deployment and maintenance of AI systems across the organization., * Assist in the design, development, and deployment of AI and GenAI solutions for AXA entities
- Collaborate with data scientists, data engineers, and product teams to understand requirements and contribute to technical solutions.
- Follow established standards and best practices for AI engineering to ensure scalable, reliable, and ethical AI systems.
- Support the deployment of AI solutions on platforms such as the Agentic platform, contributing to broader AI capabilities.
- Contribute to documentation, testing, and maintenance of AI models and systems.
- Stay updated with the latest developments in AI and GenAI technologies, applying them to ongoing projects where appropriate.
Requirements
- 3+ years delivering AI/ML-enabled products or GenAI systems, including RAG-based retrieval and agentic functionalities, in production environments.
- Demonstrated project delivery experience with some leadership in technical or project roles.
- Experience working within the insurance, financial services, or related industries is a plus.
- Proven ability to work in cross-functional teams and communicate effectively with technical and non-technical stakeholders.
Technical skills
- Good understanding of GenAI system design, including prompt engineering, retrieval workflows, context management, multi-step reasoning, and safety/privacy considerations.
- Familiarity with end-to-end AI/ML lifecycle management, including model governance, experiment tracking, deployment, monitoring, and drift detection.
- Strong software engineering skills in Python or similar languages, with a focus on scalable, production-grade AI services.
- Experience architecting scalable GenAI architectures, APIs, and system integrations.
Soft skills / transversal skills
- Collaborative team player with the ability to work in multicultural, cross-functional environments.
- Strong communication skills, capable of translating complex technical concepts into clear narratives and presentations.
- Passion to learn new techniques, research, and industry trends, with a passion for innovative GenAI applications.
- Ability to manage tasks efficiently, prioritize work, and adapt to changing project needs