"Applied Data and Financial Analytics Lecturer - Master of Quantitative Economics"

The UCLA Master of Quantitative Economics program (MQE) is looking for a Lecturer with domain expertise in Data Science, Economics, Financial Markets and Asset Pricing for Winter and Spring 2026 (January 1, 2026 - June 30, 2026). This position is non-senate and non-tenure track.

The Lecturer's main focus is to enhance the experience of MQE students with pragmatic applications of the industry's leading-edge techniques and software. The instructor will teach two lecture series, one in applied data management and one in financial analysis, for MQE students that will equip them with applied, modern data skills (2 courses in Winter quarter and 2 courses in Spring quarter).

Applicants are expected to have:

• Master's degree or higher in Quantitative/Applied Economics, Applied Finance, Data Science or a related field.
• Excellent verbal communication skills, capable of leading lectures and applied learning activities for 100+ students.
• Advanced knowledge of Python, SQL and APIs.
• Experience using Google trends and social media data in sentiment analysis for financial forecasting.
• Proficiency with Bloomberg Terminal and Bloomberg API.
• Ability to automate web scraping and predictions.
• Expertise in machine learning and predictive modeling approaches such as Random Forests, Deep learning, Super Learners, GBM, etc.
• Aptitude for creative approaches to non-standard problems.
• Experience working on applied finance or data science teams.

The University of California, Los Angeles, 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.

To apply, please visit: https://recruit.apo.ucla.edu/JPF10487