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 at http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct.

* 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.

• 3 required (contact information only)

Applicants will be asked to name references to complete their application, but the references will not be asked to provide letters unless the analyst requests them.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
• 
  UC Sexual Violence and Sexual Harassment Policy
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  UC Anti-Discrimination Policy for Employees, Students and Third Parties
• APM - 035: Affirmative Action and Nondiscrimination in Employment