Master of Applied Statistics & Data Science Adjunct Professor - Fall 2026

David Geffen School of Medicine at UCLA; Los Angeles (CA); On-site; USD 25,000 - 50,000; Full time

Job summary

The UCLA Department of Statistics and Data Science seeks open-ranked adjunct professors to teach applied statistics for the Master of Applied Statistics program for Fall Quarter 2026, starting October 1, 2026. Ideal candidates hold a Ph.D.

in Statistics or related field, demonstrate teaching excellence, and have knowledge of R, plus experience in data science, analytics, big data methods and machine learning.

Qualifications

• Ph.D. in Statistics or related field required.
• Demonstrated excellence in teaching.
• Knowledge of and experience with R.
• Experience in applied statistics, data science and analytics.
• Experience with methods for analyzing big data and machine learning.
• Commitment to excellent teaching.

Responsibilities

• Teach applied statistics in the Master of Applied Statistics program.
• Continue scholarly work through research, statistics education, consulting, or other scholarly activities.
• Temporary adjunct appointments for Fall Quarter 2026 starting Oct 1, 2026.

Skills

R

Teaching excellence

Applied statistics

Education

Ph.D. in Statistics or related field

Tools

Big data analytics

Machine learning

Job description

The UCLA Department of Statistics and Data Science seeks open-ranked adjunct professors with a strong commitment to excellence in teaching applied statistics to fill temporary positions for the Master of Applied Statistics program for Fall Quarter 2026, starting on October 1, 2026.

Ideal candidates will have a Ph.D. in Statistics or a related field, a demonstrated excellence in teaching, knowledge of and experience with R, experience in applied statistics, data science and analytics, methods for analyzing big data and machine learning, and a commitment to excellent teaching. Adjunct professors are expected to continue scholarly work, either through research in statistics education, research in statistics, statistical consulting, or other scholarly activities.

The salary range for this position is $25,000-$50,000.

All inquiries may be sent to:
Chie Ryu
UCLA Department of Statistics & Data Science
[e-mail]

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 University of California nondiscrimination and affirmative action policy.

As a condition of employment, you will be required to comply with the University of California Policy on Vaccination Programs – With Updated Interim Amendments. All Covered Individuals under the policy must provide proof of receiving the COVID-19 Vaccine Primary Series or, if applicable, submit a request for Exception (based on Medical Exemption, Disability, Religious Objection, and/or Deferral based on pregnancy or recent COVID-19 diagnosis and/or treatment) no later than the applicable deadline. All Covered Individuals must also provide proof of receiving the most recent CDC-recommended COVID-19 booster or properly decline such booster no later than the applicable deadline. New University of California employees should refer to Exhibit 2, Section II.C. of the SARS-CoV-2 (COVID-19) Vaccination Program Attachment for applicable deadlines. All Covered Individuals must also provide proof of being Up-To-Date on seasonal influenza vaccination or properly decline such vaccination no later than the applicable deadline. Please refer to the Seasonal Influenza Vaccination Program Attachment. (Capitalized terms in this paragraph are defined in the policy.) Federal, state, or local public health directives may impose additional requirements.

Ideal candidates will have a Ph.D. in Statistics or a related field, a demonstrated excellence in teaching, knowledge of and experience with R, experience in applied statistics, data science and analytics, methods for analyzing big data and machine learning, and a commitment to excellent teaching.