Senior Data Analyst

The Senior Data Analyst role is important to:

• Lead and implement Student Data Analytic Projects that aid data-informed decision-making and reporting, as well as to enhance student experience.

• Manage Student Data Catalogue and metadata in Denodo virtual data warehouse and develop integrated datasets for data analytics and reporting.

• Fully implement and enforce the Student Data Governance Framework and extensive adoption of the framework by Colleges, Schools, and Departments, that ensures data quality which is most critical for Data Analytics.

• Train end-users on new reports and dashboards.

Responsibilities

• Leading the implementation of Student Data Governance (SDG) framework across Student Admin Departments, Colleges, and Schools; Secretariat support to the SDG Steering Committee Meetings.

• Leading and conducting Data Quality (DQ) Assurance programme across different data areas and monitor DQ via developing DQ dashboard.

• Developing and managing student data catalogue for management reporting and data analytics projects.

• Driving the adoption of NTU Education Dashboards to support decision-making at different level of the University. 

• Leading, developing, and managing data analytics projects to provide enhanced insights from student data, such as student profiling, data analysis to support policy maker in relevant policies, predictive analysis of students at-risk, degree programme quality assurance analysis, student quantitative or qualitative feedback analysis using Natural Language Processing (NLP).

• Training staff in data-related framework, concepts, and competency in data analytics.

• Supporting business data users in student admin process automation.

[The role is expected to lead and facilitate, in addition to execution.]

Requirements

• Bachelor's or Master's degree in Data Science, Computer Science, or Mathematics.

• Over 7 years of professional experience in data analytics and data governance.

• Demonstrated technical proficiency in data models, database design and development, data mining, and machine learning techniques. Familiarity with Natural Language Processing (NLP) is advantageous.

• Strong familiarity with data visualization tools such as Qlik Sense, along with programming proficiency in Python/R and SQL.

• Experience with Robotic Process Automation (RPA) tools like UiPath and Power Automate is a plus.

• Proven track record in planning and executing data analytics projects to meet business objectives.

• Excellent communication skills, capable of effectively liaising with business stakeholders to understand data requirements and deliver actionable insights.