Part-Time Lecturer - MS in Applied Data Science at The University of Chicago in Chicago, Illinois

Job Description:

Description



The Data Science Institute in the Physical Sciences Division at the University of Chicago invites applications for the position of Part-Time Lecturer for the 2024-2025 academic year to teach at least one foundational, core, or elective course for the MS in Applied Data Science program. For a detailed list of courses and course descriptions, visit datascience.uchicago.edu/masters-programs.


The MS in Applied Data Science program has specific programmatic needs in Cloud Data Architecture for Data Science and AI and specialization in the financial and digital marketing domain.


This position is part-time and not benefits eligible. Applicants must currently be authorized to work in the United States.



Qualifications



Minimum qualifications:

• A Master's Degree in Data Science, Applied Math, Statistics, Computer Science, Mathematics, or other closely related field is required.
  
  


• Five years of professional experience in Data Science, Applied Math, Statistics, Computer Science, Mathematics, or other closely related field is required.
  
  

Preferred qualifications:

• A PhD in Data Science, Applied Math, Statistics, Computer Science, Mathematics, or other closely related field.
  
  


• Teaching experience either within a university (such as Adjunct, Lecturer or Instructional Professor) or corporate training environment for professional education.
  
  


• 6 years of professional experience.
  
  


• Experience teaching for an online program.
  
  

Application Instructions



To apply for this position, candidates must submit their application through the University of Chicago Jobs website: http://apply.interfolio.com/153787, and upload the following:

• CV;
  
  


• Cover letter; must list the courses you are most qualified to teach;
  
  


• A list of contact information for two references;
  
  


• Sample course syllabus;
  
  


• Teaching statement;
  
  

Optional materials: teaching evaluations from past teaching at the university level.


Review of applications will begin on October 10, 2024, and continue until the position is filled. Apply Now