Professor of Data Analytics

7 days ago

Blacksburg, Virginia, United States Commonwealth of Virginia Full time

About the Role

We are seeking a highly qualified Professor of Practice to join the Virginia Tech Academy of Data Science. As a Professor of Practice, you will play a key role in the development and delivery of our degree programs, including the Master of Science in Data Science and the undergraduate degree in Computational Modeling and Data Analysis.

Responsibilities

  • Develop overall programmatic content and concentrations for the Academy's degree programs, informed by your experience in industry and academia.
  • Develop new courses in data analytics, data-driven applications, industrial applications, and communications in technical settings.
  • Teach courses in either of the degree programs, depending on demand.
  • Workload consisting of 90% teaching and/or research and 10% service.
  • Engage with external organizations in the private sector and with government agencies to define and execute student capstone projects.
  • Mentor students in support of their capstone project activities.
  • Develop and nurture relationships outside of academia to result in internship and job placement activities for our students and partnership opportunities for the Academy.
  • Advise and mentor students in the Academy's degree programs.
  • Support other faculty who are seeking external funding opportunities.
  • Cooperate with the College of Science Advancement team to foster external relationships and identify opportunities for new partnerships.
  • Maintain knowledge of other programs and future industry needs to advise the Academy of Data Science Director and College of Science Dean on new opportunities and directions.

Requirements

  • Strong background in data analytical/mathematical/statistical methods and/or computational science.
  • Demonstrated record of achievement solving interdisciplinary problems in a business, government, or academic setting.
  • Leadership experience in this context is required.
  • Excellent communication skills with the ability to build, nurture and maintain relationships with external stakeholders.
  • Commitment to equity, inclusion and diversity.
  • PhD or Masters level degree in statistics, computer science, applied mathematics or a related field as applied to data science.

Preferred Qualifications

  • Substantial experience in business and/or government.
  • Experience working in or with a variety of industries, organizations, and/or disciplines.
  • Experience teaching graduate, undergraduate, and/or professional students, and mentoring student projects or research experiences.
  • Doctorate degree in data science, statistics, computer science, applied mathematics or related fields as applied to data science.

About Virginia Tech

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 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 colleges, a graduate school, a veterinary medicine college, a college of natural resources, and a college of architecture and urban studies. The university has a significant presence across Virginia, including the National Capital Region in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous research and outreach centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

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, 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.

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