Teaching Assistant (Quantitative Reasoning with Data)

National University of Singapore

unknownPosted Mar 5, 2026
Posting intelligenceMay be filled, listed long ago

Skills

rstudiopythonexcel

About the role

Job Title: Teaching Assistant (Quantitative Reasoning with Data)

University-Level Unit: Office of the Provost

Faculty/Department-Level Unit: General Education Unit

Employee Category: Other Teaching Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 05/03/2026

Job Description

We are seeking passionate and articulate individuals with a strong desire to empower young minds in Data Literacy. GEA1000 Quantitative Reasoning with Data, the default NUS course for Data Literacy, equips learners with essential quantitative reasoning skills to ask questions, make sense of data, and propose actions for real-world applications across diverse fields like science, engineering, healthcare, and business. The course utilizes the Problem-Plan-Data-Analysis-Conclusion (PPDAC) cycle and software packages (such as Radiant) for hands-on data analysis, visualization and actionable insights generation

Responsibilities:

In collaboration with the Departments of Statistics and Data Science, and of Mathematics, the Provost Office seeks Teaching Assistants/Course Instructors to lead engaging tutorial classes for GEA1000. Responsibilities include:

Leading engaging tutorial classes under the guidance of the Course Coordinator

Monitoring student performance, supervising group projects, and providing timely support to improve student learning outcome

Designing and implementing new teaching materials and assessment tasks

Grading assignments and assessments to evaluate student competency with prompt and constructive feedback to student

Course materials and training will be provided.

Qualifications

A Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Engineering, Business Analytics or Economics) from a reputable university

Familiarity with common data analysis tools and software (e.g., Excel, RStudio, Python, Radiant or equivalent) is preferred

Interest and ability for quantitative thinking. Prior experience in scientific research or data scientist/engineer role is an advantage

Interest and experience in teaching or mentoring students in a quantitative field is a plus

Benefits:

Competitive salary commensurate with role

Professional development opportunities, including the possibility to pursue a master’s or PhD degree

Flexible work schedule outside of teaching semesters

More Information

Location: Kent Ridge Campus

Organization: Office of the Provost

Department : General Education Unit

Employee Referral Eligible: No

Job requisition ID : 31965

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