Job Description

Columbia University, School of Professional Studies (SPS) seeks candidates to serve as a Course Associate to support the successful delivery of an on-campus graduate-level course. A Course Associate is a faculty line junior to a Lecturer, who provides subject matter expertise and supports the instructional process for a course section. Serving as a Course Associate is an excellent way to gain exposure to graduate-level teaching at Columbia University.

The course is Data Analysis and Visualization in Sustainability and it will run during the fall semester. Candidates must be available for in-person support on Tuesdays from 6:10pm to 8:00pm EST. The semester begins on Tuesday, September 5th and ends on Monday, December 11th.

Data science is an exciting new field of applied research that takes advantage of the ever-growing volume of data being collected to support of decision-making in both the public and private sectors. Similar to traditional statistical analysis, these new approaches have limits and issues that are important to understand before application to problem solving. This course aims to introduce the common methods used in data science, best practices in data management, and the basic scripting skills required to start analyzing data in R and Python. After introducing foundational scripting and data analysis methods, a case study approach will be used to highlight both what can be accomplished with data analysis and the limits of the data and methods used. Lab exercises will teach basic skills in scripting in Python and R and then move to a common approach for data analysis: adapting existing scripts and software libraries to solve applied data problems.

The requirement to understand the interaction of social and natural systems requires data-driven policy decisions, and the ongoing assessment of policies requires rigorous, reproducible assessments of effectiveness for promoting sustainability. Both requirements can be met in part by data science approaches that are applicable to the natural and social sciences and reproducible in academic and applied settings. Data science techniques have been developed to derive insight from large volumes of available data that are often collected for purposes other than the interests of the data scientist. This flexibility in approach means that the techniques used in data science are well adapted to support gaining insights from data relevant for sustainability science. This course has been designed to introduce these techniques in anticipation of increased use in promoting sustainability.

The M.S. in Sustainability Management program is designed for those who wish to pursue a career in management that takes integrates sustainability considerations into economic activity. Graduates work to transform public and private organizations and governments by formulating and implementing tailored sustainability strategies. The coursework combines the study of management with classes in sustainability practice and science, with full-time and part-time options for those with current professional obligations. Students in the program learn the use of policy and management tools to address environmental impacts and risks, pollution control, and remediation to achieve sustainability.

Responsibilities

• Attend weekly class sessions, assist with instruction, lead breakout sessions, and facilitate discussions.
• Hold weekly office hours.
• Evaluate performance, grade student work, and provide effective feedback as requested by the course Lecturer.
• Monitor and address student concerns and inquiries.
• Build working relationships with the students, provide guidance and mentoring, and respond to their inquiries in a timely manner.

Qualifications

Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.

• Graduate degree in an environmental or sustainability field.
• A background in data analysis and visualization tools.
• Expertise in the topics covered in the course.

Preferred Skills & Experience

• Project management and presentation skills, mentorship.
• University teaching experience is preferred, but not required.

Additional Information

Compensation : $3,150 for course.

All applicants, please provide:

• Resume/CV, inclusive of university teaching experience -- highlight teaching at the graduate level
• If applicable, please submit any evidence of teaching effectiveness (student evaluations, teaching observations, etc.)