Data Science Instructional Specialist

Job Description The Virginia Tech Academy of Data Science seeks a Data Science Instructional Specialist to support the development, modernization, and delivery of high-quality hybrid and online learning experiences for working professionals in data science as we expand our offerings of the MS in Data Science Degree. This position plays a critical role in converting existing and new graduate-level course content into engaging, accessible, and professionally produced online materials aligned with best practices in adult education. The Data Science Instructional Specialist collaborates closely with faculty, instructional designers, and program leadership to produce concept videos, code demonstration videos, learning assets, and assessments that support flexible, high-impact learning for students balancing professional and academic responsibilities. Fully remote work may be considered. Required Qualifications Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a closely related quantitative field. Demonstrated experience developing or supporting online or hybrid higher-education courses, particularly in technical or quantitative domains related to data science. Proficiency with Canvas or a comparable learning management system. Hands‑on experience using Camtasia or similar software for video recording, editing, and instructional content production. Strong technical communication skills, with the ability to explain complex data science concepts clearly and effectively. Experience working collaboratively with faculty, instructional designers, or academic program teams. Proficiency with Microsoft Office 365 and Microsoft Teams. Preferred Qualifications Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a closely related quantitative field. Experience supporting graduate-level or professional education programs. Familiarity with adult learning theory and instructional best practices for working professionals. Experience producing code-focused instructional content (e.g., Python, R, SQL, data visualization). Knowledge of accessibility standards for online learning (e.g., captions, transcripts, universal design). Prior experience in data science, analytics, or computational research consulting organizations that solve applied problems. Comfort working in fast-paced production cycles with defined timelines and deliverables. Coursework in machine learning, statistical/data science computing, and communication. Developing and teaching data science-related short courses to applied problem solvers outside traditional data science fields. Experience creating course content using large language models such as ChatGPT, Claude, Google LLM and Natural Reader (or similar text to speech software). Experience using a markdown language (R‑markdown, Quarto, etc.) to create slides, reports, and/or graphics. Experience as a teaching assistant, instructor, or professor in an academic setting. Overtime Status Exempt: Not eligible for overtime Appointment Type Regular Salary Information Starting at $70,000 - commensurate with experience Hours per week 40 hours - exempt position Review Date 03/13/2026 Additional Information The successful candidate will be required to have a criminal conviction check. Equal Employment Opportunity Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law. Accommodations for Individuals with Disabilities If you are an individual with a disability and desire an accommodation, please contact Holly Caldwell at View email address on click.appcast.io during regular business hours at least 10 business days prior to the event. #J-18808-Ljbffr Virginia Polytechnic Institute and State University (VT)