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Lecturer, "Machine Learning/Data Science"

Recruitment Period

Open September 12th, 2018 through Sunday, Jun 30, 2019 at 11:59pm (Pacific Time)


The Master of Applied Economics Program at UCLA is seeking a part-time lecturer for either the Winter and Spring 2019 quarters or both (January – June 2019).

The candidate will be expected to teach a class on Machine Learning/Data Science to a maximum of 70 students who are enrolled in a graduate economics program.

The candidate will provide instruction to students introducing them to Exploratory Data Analysis, Machine Learning, Big Data Processing, Sentiment Analysis, and Multi-dimensional Data Visualization--with a specific focus on problems in Applied Economics.

The candidate will teach R Programming Language for enabling students to solve data analysis and basic Machine Learning algorithms including: Linear Regression, Naive-Bayes, Clustering, and Classification, and Tableau for Data Visualization. The Candidate will also teach the importance of Data Science as a discipline in multiple application domains.

The candidate will address Data Privacy and Regulatory Compliance in the use of data.

The candidate will teach an introductory course in Winter quarter and/or an intermediate course in Spring quarter.

Candidates are encouraged, but not required, to submit their recommended textbooks and readings for the course.

Candidates must have a Master’s degree or higher.

Candidates should apply through UC Recruit:

The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: UC Nondiscrimination & Affirmative Action Policy.

Job location

Los Angeles, CA


Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter

  • List of your Recommended Textbooks/Readings for the Course (Optional)

  • Statement of Research (Optional)

  • Statement of Teaching (Optional)

  • Statement of Contributions to Diversity - Statement addressing past and/or potential contributions to diversity through research, teaching, and/or service.

  • Misc / Additional (Optional)

Reference requirements
  • 3-5 required (contact information only)