•Data Governance: Develop and implement a data governance framework to ensure data quality, consistency, security, and compliance.

•Data Analysis and Mining: Use data analysis tools and techniques to extract insights from business data, supporting business decision-making(E.g. Assisting for TPP analysis etc.).

•Data Science and Machine Learning: Develop and deploy machine learning models to drive business intelligence (E.g. predictive maintenance & anomaly detection in shopfloor).

•Data Quality Management: Monitor data quality, establish data quality metrics, and regularly assess the health of data.

Professional Knowledge:

- Familiarity with data governance frameworks (e.g., DAMA-DMBOK, DCAM, etc.).

- Proficiency in data analysis methods (e.g., statistical analysis, visual analysis, etc.) and data science techniques (e.g., machine learning, etc.).

Technical Skills:

- Proficient in data analysis tools (e.g., Python, R, SQL, Tableau, Power BI, etc.). And Familiarity with data science tools and frameworks (e.g., TensorFlow)

- Knowledge of data governance tools (e.g., Collibra, etc.). And Possess basic programming skills and the ability to collaborate with development teams.

Communication and Collaboration Skills:

- Ability to effectively communicate with various stakeholders and capable of cross-departmental collaboration and project management.

Transformation Management Skills:

- Ability to drive organizational change and enhance the team's acceptance and execution of data governance and data analysis.

- Possess training and educational capabilities to empower team members.