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.

Fully remote work may be considered.

• 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.

• 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 markdown languages (R‑markdown, Quarto, etc.) to create slides, reports, and/or graphics.
• Experience as a teaching assistant, instructor, or professor in an academic setting.

Exempt:
Not eligible for overtime

Regular

Starting at $70,000 - commensurate with experience

40 hours - exempt position

03/13/2026

The successful candidate will be required to have a criminal conviction check.

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands‑on, transdisciplinary approach to preparing scholars to be leaders and problem‑solvers. A comprehensive land‑grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College.

The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared…