The Data Scientist Apprentice – AI & Digital Innovation contributes to the identification, development, experimentation, and deployment of solutions based on Data Science, Machine Learning, and Artificial Intelligence.
Beyond technical development, they act as a true Technology Scout, responsible for exploring market trends, evaluating emerging technologies, and contributing to the continuous improvement of the company’s Data & AI practices.
They are responsible for technology watch activities, identifying new innovation opportunities, and sharing knowledge across teams to accelerate the adoption of best practices and emerging solutions.
Their role also includes systematically documenting discoveries, experiments, and achievements to facilitate knowledge reuse by other developers and contributors within the digital ecosystem. #JT
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Identify and analyze opportunities to leverage Data Science and Artificial Intelligence to address business challenges.
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Participate in the design and development of high-value AI use cases.
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Develop and test prototypes, demonstrators, and Proofs of Concept (PoCs).
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Contribute to the evaluation and improvement of developed models.
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Support the industrialization and deployment of validated solutions.
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Assist project managers in tracking and monitoring Data & AI initiatives.
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Conduct continuous technology watch on Data, AI, Generative AI, Machine Learning, Agentic AI, MLOps, and analytics platforms.
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Identify emerging trends, products, frameworks, methodologies, and tools.
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Test and evaluate innovations to assess their potential value for the organization.
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Monitor the evolution of the company's technology platforms and analyze the impact of new features and capabilities.
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Provide recommendations on technologies to adopt or experiment with.
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Be able to quickly provide a clear view of major market innovations and their applicability within the company’s context.
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Explore new ways to connect the company’s tools, platforms, and data sources.
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Develop integrations, automations, and connectors to streamline interactions between systems.
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Investigate the use of APIs, AI agents, and modern architectures that enhance solution interoperability.
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Contribute to the continuous improvement of the digital ecosystem and its operational efficiency.
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Identify automation opportunities to improve team productivity.
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Systematically document developments, experiments, and implemented architectures.
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Create technical guides, tutorials, best-practice documentation, and lessons learned.
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Contribute to the creation and maintenance of a Data & AI knowledge base.
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Support team upskilling by sharing insights and learnings from experiments.
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Ensure that completed work can be easily understood, maintained, and reused by other developers.
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Simplify and explain concepts related to AI, Data Science, and emerging technologies.
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Regularly present experiment results and technology trends.
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Contribute to Data & AI awareness and adoption across business and technical teams.
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Promote a culture of innovation, continuous learning, and knowledge sharing.
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Act as a bridge between technical experts and business users.
