Part-Time Faculty of Business Analytics - BAT 3302-1 - Data Science
Trinity University
·Yesterday
- Location
- Trinity University Campus, United States of America
- Type
- Part-time
- Department
- IT
- Education
- PhD
- Source
- Workday
Description
Job Family Group:
FacultyTime Type:
Part timeDepartment/Office:
Finance and Business AnalyticsExemption Status:
ExemptJob Description:
Trinity University is seeking a Part-Time Faculty for the Fall 2026 semester to teach the following course(s):BAT3302-001: Data Science
DUTIES AND RESPONSIBILITIES
Typical responsibilities of part-time faculty members include but are not limited to:
Developing the course syllabus and ensuring that the syllabus meets departmental and University standards
Designing and delivering lectures, discussions, in-class activities, and assignments focused on the storage, retrieval, and analysis of data sets. This course places strong emphasis on data wrangling using Python and the practical application of specialized software, computational techniques, and algorithms to real-world business and analytical scenarios. The ideal candidate combines academic grounding in data science methods with hands-on industry experience applying these tools to solve practical problems.
Grading assigned papers, quizzes, and exams
Assigning early, midterm, and final grades in compliance with University deadlines
Maintaining office hours as directed by the department chair or program director
Making student accommodations as determined by the Office of Student Accessibility Services
Adhering to all instructional policies as published in the Faculty Handbook and the Courses of Study Bulletin
QUALIFICATIONS
EDUCATION
Required:
Master's degree in Data Science, Business Analytics, Computer Science, Statistics, or a closely related field
Preferred:
Ph.D. in Data Science, Business Analytics, Computer Science, Mathematics, Statistics, or a closely related field
EXPERIENCE
Required:
Professional or applied experience in data analysis, data wrangling, or working with large data sets
Proficiency in Python
Preferred:
Prior university-level teaching experience, particularly in analytics or data science courses
Evidence of impactful teaching practice demonstrated through submission of sample teaching materials and student evaluations.
Industry experience applying data science techniques to business decision-making
Familiarity with data visualization tools and learning management systems (e.g., Canvas, Blackboard)
KNOWLEDGE/SKILLS/ABILITIES
The ideal candidate will demonstrate:
Mastery of the relevant subject matter
Ability to deliver engaging lectures, discussions, or in-class activities
Ability to design rigorous and meaningful assignments
Commitment to the liberal arts mission of Trinity University
HOW TO APPLY
For internal applicants, please apply through Workday using the 'Jobs Hub' application, see instructions provided here.
For external applicants, when starting the application, select "Apply Manually.” Only complete fields with a red asterisk, which are required. Please create your Workday application account using a personal email address, as you will need to maintain access to this account throughout the pre-hire process, if selected.
For all applicants, you do not need to complete the “(Work) Experience,” “Education,” “Certifications,” or “Languages” fields - these details will be provided in your curriculum vitae.
In the “Application Documents” field, please upload the following four files, each as a separate pdf file [note: a maximum of five (5) files can be uploaded]:
File 1: Cover letter
File 2: Curriculum vitae or resume
File 3: Names and contact information for three professional references
File 4: Portfolio of teaching materials and student evaluations
CONTACT INFORMATION
All inquiries and questions should be addressed to Diana Young, Department Chair, [email protected].
Please ensure that all required documents are uploaded prior to submitting an application. If you have revisions needed to an application already submitted or need help submitting an application, please contact Human Resources at 210-999-7507 or email [email protected].