Online Visiting Professor of Data Analytics
DeVry University · Remote — United States
Remote
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Sign inJob overview
- Location
- Remote — United States
- Workplace
- Remote
- Employment type
- Part-time
- Experience level
- Mid level
- Date posted
- Oct 11, 2026
- Last checked at the source
- Oct 11, 2026
- Job source
- via Himalayas
Responsibilities
• Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives.
• Organizes, prepares, and regularly revises and updates all course materials.
• Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students.
• Models effective oral and written communications that engage the students, provide clarity, and improve student learning.
• Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories.
• Ensures that the content and level of material included on exams correspond to the course terminal objectives.
• Demonstrates consistency and fairness in the preparation and grading of exams, and provide timely feedback to students.
• Embraces and integrates the responsible use of AI technologies in the classroom to enhance teaching and learning outcomes.
• Demonstrates the ability to recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
• Completes other duties as assigned.
Requirements
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
• A doctorate in Data Analytics, Data Science, Statistics, Computer Science, Information Systems, or a closely related field is required, with at least 18 graduate credit hours in data analytics, statistics, data science, quantitative analysis, or a related computational discipline.
◦ Applicants must upload unofficial graduate-level transcripts with their application. ◦ Degrees must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or by an international institution determined to hold 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, which may include statistical software, data visualization platforms, database technologies, and programming languages used for analytics.
• Industry-recognized certifications or professional credentials relevant to data analytics, data science, business intelligence, or statistical analysis.
• Strong subject matter expertise in data analytics concepts and methodologies, combined with effective communication skills and the ability to translate complex quantitative concepts for diverse learners.
• Knowledge of ethical and responsible data practices, including data governance, privacy considerations, bias awareness, and responsible use of data in decision-making.
• Additional requirements driven by state licensing, institutional policy, or accreditation standards may apply.
• Faculty must have a commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
• Industry certifications in data analytics, data science, or business intelligence platforms (e.g., Python-based analytics certifications, data analytics practitioner credentials, or comparable industry-recognized certifications).
• Experience with data management and analytics ecosystems, including databases, data warehousing, data pipelines, and large-scale data processing envir
Skills
- Python
- Data Analysis
- Data Science
- Data Engineering
- Teaching
- Communication
Visa and relocation
The posting doesn't mention visa sponsorship. Check the original posting or ask the company.
The posting doesn't mention relocation.
Job description
DeVry University strives to close our society’s opportunity gap and address emerging talent needs by preparing learners to thrive in careers shaped by continuous technological change. Through innovative programs, relevant partnerships, and exceptional care, we empower students to meaningfully improve their lives, communities, and workplaces.
Our colleague experience is an area of obsessive focus. At DeVry University, we care about you. Because, only through you can we deliver our unique Care Formula to our learners and partners.
Opportunity:
DeVry University focuses on developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm and a commitment to providing the finest practitioner-focused education. We are seeking primarily industry professionals to teach and share their knowledge and experience with undergraduate and graduate students in a variety of fields.
• Courses meet once or twice a week for eight weeks.
• Face-to-face interaction is blended with technology (such as online discussions and online assignments) for an enhanced learning environment.
• Faculty are responsible for facilitating student learning by teaching courses and programs in accordance with DeVry University requirements.
• Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives.
• All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction.
•
DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion.
• As you explore this opportunity, we invite you to view this brief video highlighting how our faculty engage in meaningful student support.
Responsibilities:
• Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives.
• Organizes, prepares, and regularly revises and updates all course materials.
• Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students.
• Models effective oral and written communications that engage the students, provide clarity, and improve student learning.
• Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories.
• Ensures that the content and level of material included on exams correspond to the course terminal objectives.
• Demonstrates consistency and fairness in the preparation and grading of exams, and provide timely feedback to students.
• Embraces and integrates the responsible use of AI technologies in the classroom to enhance teaching and learning outcomes.
• Demonstrates the ability to recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
• Completes other duties as assigned.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
• A doctorate in Data Analytics, Data Science, Statistics, Computer Science, Information Systems, or a closely related field is required, with at least 18 graduate credit hours in data analytics, statistics, data science, quantitative analysis, or a related computational discipline.
◦ Applicants must upload unofficial graduate-level transcripts with their application. ◦ Degrees must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or by an international institution determined to hold 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, which may include statistical software, data visualization platforms, database technologies, and programming languages used for analytics.
• Industry-recognized certifications or professional credentials relevant to data analytics, data science, business intelligence, or statistical analysis.
• Strong subject matter expertise in data analytics concepts and methodologies, combined with effective communication skills and the ability to translate complex quantitative concepts for diverse learners.
• Knowledge of ethical and responsible data practices, including data governance, privacy considerations, bias awareness, and responsible use of data in decision-making.
• Additional requirements driven by state licensing, institutional policy, or accreditation standards may apply.
• Faculty must have a commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
Preferred Qualifications
• Industry certifications in data analytics, data science, or business intelligence platforms (e.g., Python-based analytics certifications, data analytics practitioner credentials, or comparable industry-recognized certifications).
• 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
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