Hiring.Camp

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:

Faculty

Time Type:

Part time

Department/Office:

Finance and Business Analytics

Exemption Status:

Exempt

Job 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].

Skills

PythonData ScienceWorkdayCompliance

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