Manager, Data Analytics

About the role

The Student and Academic Services Department (SASD) of NTU is looking for a hands-on analytics professional to join its Digital Innovations Team. The team builds AI-enabled solutions, automates administrative processes and delivers data-driven insights to improve staff efficiency and student experience. The role covers BI, analytics and applied AI end to end, guides junior team members and suits someone with strong problem-solving and communication skills in a cross-functional environment.

Key responsibilities

• Lead data analytics and AI projects independently, from problem definition and data exploration through solution development, evaluation and implementation.
• Develop and oversee BI dashboards and reporting solutions, with hands-on support for complex requirements.
• Analyse data and build decision-support solutions that turn data into actionable insights; experience with AI-enabled analytics or analytics agents is an advantage.
• Develop and evaluate AI solutions such as RAG, AI-enabled workflows and AI agents where relevant to business needs.
• Apply data science approaches such as forecasting, predictive analytics or recommendation to support business decisions.
• Work with technical teams to integrate analytics and AI solutions into operational workflows and existing platforms.
• Guide junior team members in dashboard development, data analytics, analytical problem solving and emerging AI-enabled analytics approaches.

Required profile

• Bachelor's or Master's degree in Data Science, Business Analytics, Computer Science, Information Systems, Engineering, Mathematics, Statistics or a related discipline, or equivalent relevant experience.
• Typically 5-8 years of professional experience in data analytics, business intelligence, data science or related areas, with the ability to own and deliver projects independently.
• Ability to communicate analytical and technical work clearly to non-technical stakeholders and to work independently in a dynamic, cross-functional environment.

Required skills

• Strong SQL and Python, with data analysis using pandas, NumPy and scikit-learn.
• Dashboards and analytical solutions in Power BI, Qlik Sense, Tableau or similar BI platforms.
• Experience with forecasting, predictive analytics, recommendation or other applied data science use cases.
• Practical exposure to Generative AI applications such as RAG, AI workflows or AI agents; familiarity with LangChain/LangGraph, Microsoft Agent Framework or Google ADK is an advantage.
• Cloud-based data, analytics or AI platforms, with Microsoft Azure experience preferred.