Job description
Summit University invites applications for a full-time Lecturer in Data Science in the Department of Computer Science. This role emphasizes high-quality teaching, innovative curriculum development, and active student mentorship across undergraduate and graduate programs.
We seek a candidate with a passion for data-driven education, strong communication skills, and a commitment to inclusive pedagogy that supports diverse learners. The successful candidate will contribute to course delivery, assessment design, and collaboration with faculty on program improvements.
Responsibilities include teaching core data science courses, developing engaging labs, advising students, and contributing to scholarly activities that enhance the department's teaching mission.
Responsibility
- Deliver high-quality lectures and labs for undergraduate and graduate Data Science courses with an emphasis on practical, project-based learning.
- Design, update, and assess course materials, syllabi, and assessments to align with program outcomes.
- Mentor and advise students; provide timely feedback and support for academic success.
- Lead or co-lead laboratory components, data projects, and capstone experiences.
- Collaborate with faculty on curriculum development and program evaluation.
- Incorporate inclusive teaching practices and accessible learning strategies to support a diverse student body.
- Engage in scholarly activity related to teaching and learning in data science, and contribute to departmental service.
Qualification
- Master's degree in Data Science, Computer Science, Statistics, or a closely related field; PhD preferred for higher-level instruction.
- Proven teaching experience in higher education and the ability to teach in person and online.
- Strong command of data science tools including Python, R, SQL, and data visualization libraries.
- Experience with curriculum design, learning outcomes assessment, and quality improvement.
- Excellent communication, collaboration, and mentorship skills; commitment to inclusion and equity in the classroom.
- Active engagement in scholarly activity or professional practice related to data science is a plus.