4. Expert

•AI Knowledge: Masters modern and complex AI algorithms, has deep knowledge of techniques such as deep learning, NLP, computer vision.

•Technical Skills: Can develop high-performance models, deploy and manage models in production environments.

•Problem Solving: Solves complex and multi-dimensional problems, optimizes models and produces innovative solutions.

•Data Literacy: Uses big data platforms (Spark, Hadoop, etc.) effectively and is an expert in real-time data analytics.

•AI Ethics: Systematically prevents bias and ensures ethical compliance by applying AI ethics in projects.

•Communication and Collaboration: Takes a leadership role in projects and communicates effectively with senior management and non-technical stakeholders.

•Application and Industry Knowledge: Has in-depth application experience in specific sectors and solves problems in the sector with innovative approaches.

•Continuous Learning: Closely follows research and innovation and contributes to sectoral developments.