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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 students
Course materials and training will be provided.
Qualifications
Prerequisites:
- 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
