Subject Matter Expert – Data Science

Subject Matter Expert – Data Science


Part Time



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Excelsior University is recruiting Subject Matter Experts (SME) on a contractual basis to support individual course development. The SME will have advanced knowledge and expertise in computer science and Data Science. Courses to be developed or revised may include: (1) Ethical Data Wrangling and Processing, (2) Predictive Analytics and Time Series Forecasting, (3) Predictive Analytics and Time Series Forecasting, (4) Big Data Analytics, (5) Foundations of Data Science.

Reporting to the Department Chair, the SME plays a key role in the design and revision of course content. The SME works closely with the Department Chair, Learning Experience Designer, and other staff across the University during the course development process. The course development process lasts about 20-weeks/4.5 months, unless it is an expedited development. This timeline does not include the Excelsior onboarding and compliance training.

Duties and Responsibilities: 
  • Update an existing course or design a new course based on area need, including program content and materials and/or delivery methods, and based on foundational knowledge, emerging practices, changes in the discipline, etc.
  • Align course development with course and program learning outcomes. Thematic areas may include:
  • Possess the ability to identify relevant learning resources and content.
  • Create engaging learning activities, assignments, and valid assessments of learning.
  • Ensure that the course curriculum aligns with Excelsior’s justice, equity, diversity, and inclusion (JEDI) principles.
  • Commit to being available throughout an agreed upon course development timeline and able to meet project deadlines.
  • Participate in weekly or bi-weekly course development meetings.
  • Collaborate with the course development team throughout the design process.
  • Use the Excelsior University course shell as the framework for the course.
  • Write lectures, assignments, rubrics, and provide original content in an editable format.
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.
  • An earned doctorate, or a master's degree and significant professional experience in the field, ideally in the field of computer science, or another field relevant, and a background in Data Science, to supporting the program and its courses.
  • Demonstrated significant industry and/or experience in the field of Data Science.
  • Teaching experience at a two- or four-year degree granting institution in computer science or a related field preferred.
  • Familiarity with the development and implementation of curriculum and/or training computer science.

Remote applicants please be aware that the University is required to withhold New York state income taxes from your wages, as well as the state income tax, if applicable, in the state where you perform services. This is because of New York’s “convenience of the employer” rule, which requires the University, as a New York employer, to withhold New York income tax from the wages of its employees working outside of New York if the employee’s work is performed outside of New York for the convenience of the employee, rather than out of a business necessity of the University.

Application Information

If you have problems with online submission, please call 518-608-8270.

Excelsior University offers competitive compensation and a generous benefits package that includes paid time off, retirement, and excellent health insurance. Interested candidates should submit a letter of application, resume, and the names of three professional references. Please submit requested information by clicking the Apply Now button on this page.


Excelsior University is an equal opportunity employer committed to ensuring all qualified applicants receive consideration for employment without regard to any legally protected characteristic.

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