Lecturer, Data Science (Temporary Employee Pool)

University of the Pacific; Stockton; On-site; CAD 70,760 - 84,757; Part time

Job summary

The University of the Pacific seeks a part-time Lecturer in Data Science for the Fall 2026 semester to lead a course in Customer Analytics. The position involves teaching an asynchronous online course and engaging in experiential learning practices.

Applicants are expected to have a Master's or Ph.D. in a related field and demonstrate experience in retail analytics and consumer data modeling. Responsibilities include organizing course materials, producing video lectures, and grading assignments while supporting student interactions online.

Qualifications

• Demonstrated experience in retail analytics, e-commerce, or consumer data modeling.
• Commitment to experiential learning and ability to translate technical concepts into business value.

Responsibilities

• Organize course content and materials for a data science course.
• Produce weekly video lectures aligned with learning outcomes.
• Design and grade weekly assignments and provide online office hour support.

Skills

Data Science

Retail Analytics

Consumer Data Modeling

Education

Master’s or Ph.D. in Data Science, Computer Science, Business Analytics, or a related field

Job description

Primary Purpose And Essential Functions

Position: Lecturer, Data Science (Temporary Employee Pool) – part-time, 3 days per week, 15 weeks – Fall 2026 semester.
The University of the Pacific is seeking a dynamic and data-driven Adjunct Faculty member to lead a specialized, one-unit experiential learning course in Customer Analytics for the Fall 2026 semester. The School of Engineering and Computer Science at the University of Pacific invites applications for a part-time, non-tenure track Lecturer position in the Data Science Department. The lecturer will teach a 1-unit, 15-week asynchronous online course for the Master of Science in Data Science program. Responsibilities include organizing course content and materials, producing weekly video lectures aligned with the course’s learning outcomes, designing and grading weekly assignments, providing online office hour support to students, and creating and coordinating project work for the weekly, in‑person, 3‑hour Data Science Socratic Lab.

Courses to be taught: Customer Analytics.

Qualifications

• Master’s or Ph.D. in Data Science, Computer Science, Business Analytics, or a related field.
• Demonstrated experience in retail analytics, e-commerce, or consumer data modeling.
• Commitment to experiential learning and ability to translate technical concepts into business value.

Preferred Qualifications

• Knowledge and experience in data science, specifically customer analytics.
• Experience and sensitivity in working with people of diverse backgrounds and cultures.
• Demonstrated experience in advancing social justice, equity, and inclusion in a university setting.
• Ability to engage and integrate culturally responsive practices and knowledge.

Physical Requirements

Requires extended periods of sitting and repetitive hand/wrist motion while using a computer keyboard and phone. Occasional standing, walking, climbing stairs, bending, stooping, and reaching. Occasional lifting of up to 25 pounds.

No Visa Sponsorship

This position is not eligible for visa sponsorship now or in the future.

Hiring Range

$5,000.00 per unit.

Contact Information

Dr. James Hetrick, Professor/Director of Data Science.
email: [e-mail]

Anti‑Discrimination/EEO Policy Statement

University of the Pacific is an equal opportunity employer dedicated to workforce diversity across backgrounds, experiences, and viewpoints. Pacific does not unlawfully discriminate in its hiring of faculty and staff, or in the provision of its employment benefits to its faculty and staff on the basis of race, color, religion, national origin, ancestry, age, genetic information, sex/gender, marital status, military and veteran status, sexual orientation, medical condition, pregnancy, gender identity, gender expression, or mental or physical disability, or other legally protected characteristics or combination of such characteristics. While we strive to attract a broad and representative pool of candidates, all hiring decisions are made based on merit, selecting the most qualified individual for each position.