Online Visiting Professor of Data Analytics

DeVry University

7d•$1,500 - $2,700•Remote

About The Position

DeVry University seeks industry professionals to teach undergraduate and graduate students and share their professional knowledge and experience. Faculty facilitate student learning in accordance with university requirements, develop syllabi and lesson plans, and use teaching techniques aligned with course and program objectives. Courses meet once or twice per week for eight weeks and blend face-to-face interaction with technology, including online discussions and assignments. Faculty participate in comprehensive training and ongoing development. The university does not guarantee a specific number of work hours or teaching assignments; these may vary according to university needs and discretion.

Requirements

Doctorate in Data Analytics, Data Science, Statistics, Computer Science, Information Systems, or a closely related field.
At least 18 graduate credit hours in data analytics, statistics, data science, quantitative analysis, or a related computational discipline.
Upload unofficial graduate-level transcripts with the application.
Degrees must be from an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or from an international institution determined to have equivalent accreditation.
Three to five years of applied professional experience in data analytics, data science, business intelligence, statistical analysis, or data-driven decision support.
Demonstrated experience with data analysis tools and programming environments, potentially including statistical software, data visualization platforms, database technologies, and analytics programming languages.
Industry-recognized certifications or professional credentials relevant to data analytics, data science, business intelligence, or statistical analysis.
Strong expertise in data analytics concepts and methodologies, effective communication skills, and the ability to explain complex quantitative concepts to diverse learners.
Knowledge of ethical and responsible data practices, including data governance, privacy, bias awareness, and responsible use of data in decision-making.
Commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
Additional requirements may apply based on state licensing, institutional policy, or accreditation standards.

Nice To Haves

Industry certifications in data analytics, data science, or business intelligence platforms, such as Python-based analytics certifications, data analytics practitioner credentials, or comparable credentials.
Experience with data management and analytics ecosystems, including databases, data warehousing, data pipelines, and large-scale data processing environments.
Experience applying analytics frameworks and methodologies, such as predictive analytics, exploratory data analysis, statistical modeling, and data visualization.
Experience with data governance and data lifecycle management, including data quality, compliance, and responsible data stewardship.
Experience with programmatic or regional accreditation processes, including outcomes assessment, curriculum alignment, and continuous improvement.
Active membership or engagement in professional analytics, statistics, or data science organizations.
Experience integrating analytics laboratories, real-world datasets, and analytics platforms into post-secondary instruction.
Two to five years of post-secondary teaching experience, preferably in data analytics, statistics, business intelligence, database management, or related disciplines.

Responsibilities

Develop and provide students with an approved DeVry University syllabus using the local campus template and including terminal course objectives.
Organize, prepare, regularly revise, and update course materials.
Use appropriate online technologies and course-related software, including websites, email, and online discussions, to prepare courses and make them accessible to students.
Model effective oral and written communication that engages students, provides clarity, and supports learning.
Set clear course expectations by publishing terminal objectives, assignment and examination dates, and the weighting of evaluation categories.
Ensure exam content and difficulty correspond to course terminal objectives.
Prepare and grade exams consistently and fairly, and provide timely feedback to students.
Integrate the responsible use of AI technologies to enhance teaching and learning outcomes.
Recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
Complete other duties as assigned.