Adjunct Faculty (Data Science and Artificial Intelligence) NLC - req13794

Adjunct Faculty (Data Science and Artificial Intelligence) NLC - req13794

To receive consideration for employment, you must upload transcript(s) and a Resume/CV. Please submit transcript(s) under "Other Documents" under applicant profile in application.

Posting closes on: 12/1/2026 at 6:00pm CST

The date after which applications are not guaranteed review is 12/1/2026

This position is part-time and temporary

Employment type: TN

Hours per Week: Varies

Hourly or Salaried: Salary

Entry Pay: Depends on education level

Funding source: Hard Money

Benefits Eligible: No

Location: Data Sci Artificial Intelligenc

1201 Kitty Hawk Rd.

Universal City, Texas, 78148

United States

Requisition #: req13794

Outside working hours if other than M-F 8:00 a.m. to 5:00 p.m.: May work evenings and weekends

Job Summary and Description

Teaching faculty are professional educators who have the primary responsibility of fulfilling the District mission of providing a quality education for all students attending the colleges. Categories include full-time, temporary with benefits, and temporary without benefits. Faculty members are responsible to a department/program chairperson; The relationship of the faculty member to the student is one of leader, teacher, advisor, and facilitator of learning. Faculty members will uphold the mission and values of the colleges' and foster effective working relationships with students and colleagues.

To view a complete job description, click here.

Qualifications

Minimum Education and Experience:

• Associates degree plus three years of experience.
• Python coding with experience in Pandas, Scikit, numpy.
• Experience with IDEs such as PyCharm and Anaconda.
• Experience in Machine Learning, supervised and unsupervised, including creation of small models for real-world purposes.
• Familiarity with frameworks such as TensorFlow.
• Exposure to Neural Networks/Deep Learning Algorithms.
• Good understanding of statistics (regression, ANOVA).
• Fair knowledge of RDBMS, NoSQL, JSON, YAML.
• Some Experience with benchmarking LLMs qualitatively and quantitatively.

Preferred Education and Experience:

• Some R knowledge would be preferred.

EEO Statement