Columbiauniversity1

Columbiauniversity1

Adjunct Associate Faculty, Analytics for Business Operations Management (On-Campus, Fall '26)

New York, NY, United States · Part-time

Sponsorship not specifiedDetected 145 days ago
PythonPandasNumPyData AnalysisData ScienceProject ManagementForecastingOperations ManagementSupply ChainResearch

About the role

  • Columbia University has been a leader in higher education in the nation and around the world for more than 250 years.
  • At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society.
  • The School of Professional Studies seeks candidates to serve as a part-time Associate for a graduate- level course in Analytics for Business Operations Management.

Responsibilities

  • Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions.
  • Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions.

Requirements

  • Graduate degree in an area related to Operations Management, Business Analytics, Industrial
  • 3+ years of professional experience in a role involving applied analytics, operations
  • Strong understanding of Operations Management concepts such as forecasting, queuing theory,
  • Proficiency in data analysis using Python and familiarity with tools such as Jupyter Notebook,
  • Experience applying Python to real-world operations management problems.
  • Ability to mentor students and provide constructive feedback on analytical work.

Nice to have

  • Preferred Skills & Experience

Compensation

  • $2,000 - $3,000 per semester long course
  • Please submit a resume inclusive of university teaching experience.

Equal opportunity

  • All your information will be kept confidential according to EEO guidelines.
  • Equal Opportunity Employer / Disability / Veteran

This listing is sourced directly from Columbiauniversity1's careers page and normalized into a canonical job model.