Part Time Lecturer - Analytics (Arlington)

Northeastern University•Arlington, VA

About The Position

The College of Professional Studies at Northeastern University invites applications for a non-tenure-track, part-time faculty lecturer in Analytics at the Arlington campus. The College offers undergraduate, graduate, and doctoral programs on campus and online, with an emphasis on lifelong experiential learning. The lecturer will teach analytics to global student populations. Instructional areas may include probability and statistics, data exploration and visualization, database management systems, leadership and risk management in analytics, business support, and predictive analytics. The Master of Professional Studies in Analytics develops foundational skills for working professionals, including data preparation and analysis, forecasting, optimization, visualization, and data storytelling. The program is grounded in experiential learning connected to professional applications and prepares students for general entry- and mid-level analytics roles. Applicants should submit a cover letter and vitae. The cover letter should explain how their expertise, knowledge, and skills will support pedagogy and curriculum that foster belonging in the university community. Applications will be reviewed until the position is filled. Northeastern University will not sponsor an employment visa; the successful applicant must maintain valid U.S. work authorization throughout the appointment without university visa sponsorship.

Requirements

Master’s degree in an aligned discipline.
Experience in the analytics industry.
Demonstrated teaching, coaching, and/or training experience.
Ability to maintain valid work authorization in the United States throughout the appointment without Northeastern University visa sponsorship.

Nice To Haves

PhD in a sciences field, or similar.
A history of successful graduate-level teaching online and/or on ground is strongly preferred.

Responsibilities

Teach analytics courses to global student populations.
Provide instruction in relevant analytics areas, potentially including probability and statistics, data exploration, data visualization, database management systems, leadership and risk management in analytics, business support, and predictive analytics.
Contribute to experiential learning connected to professional applications in the workforce.
Develop pedagogy and curriculum in ways that reflect and enhance belonging in the university community.