Part-Time Data Science Professor — AI-Driven Labs

State of South Carolina; South Carolina; Hybrid; USD 55,000 - 83,000; Part time

Job summary

Midlands Technical College is seeking a Part-Time Adjunct Professor of Data Science to provide applied instruction across database systems, data preparation, analytics, and visualization. The instructor will modernize curricula to emphasize clean data, responsible AI use, and skills aligned with workforce needs, delivering lectures, labs, and assessments.

The position may involve teaching at multiple campuses or online formats, with courses scheduled day, evening, or weekend.

Qualifications

• Bachelor’s degree required in data science, CS, IS, MIS, analytics, statistics, or related field.
• Professional experience with relational databases, SQL, data cleaning/preparation, data analysis, BI, or related data technologies.
• Knowledge of tools such as Excel, Access, SQL Server, Power BI, Tableau.

Responsibilities

• Deliver lectures, discussions, demonstrations, labs, and assessments aligned with course outcomes.
• Prepare lessons, projects, and evaluations; provide timely feedback on student work.
• Teach data science topics including database systems, data prep, analytics, visualization, and AI ethics.

Skills

SQL

Data visualization

Data cleaning

Explain concepts clearly

Instructional skills

Education

Bachelor’s degree in data science, computer science, information systems, management information systems, business analytics, statistics, or related field

Master’s degree preferred

Tools

Power BI

Tableau

SQL Server

Microsoft Excel

Job description

Midlands Technical College is seeking a Part-Time Adjunct Professor of Data Science to provide applied instruction across database systems, data preparation, analytics, and visualization. The instructor will modernize curricula to emphasize clean data, responsible AI use, and skills aligned with workforce needs, delivering lectures, labs, and assessments.

The position may involve teaching at multiple campuses or online formats, with courses scheduled day, evening, or weekend.