Data Science Instructor – Pool – UCLA Extension

Data Science Instructor – Pool – UCLA Extension

UCLA Extension is considered one of the top programs of its kind, offering to more than 35,000 students per year approximately 4,500 classes and non-degree certificate programs to meet the professional development, continuing education, and personal enrichment needs of the full spectrum of nontraditional students as well as companies and organizations throughout and beyond the Los Angeles region.

The Engineering and Computer Science Academic Unit offers a wide variety of certificate programs and courses including post-baccalaureate credit-bearing (400-level) and continuing education (CEU) credit courses. Course disciplines span engineering, computer science and technical management subject areas. UCLA Extension courses and certificate programs offer students the opportunity to learn from highly qualified practitioners who hold advanced degrees and are passionate about teaching and can impart knowledge within their field of expertise.

UCLA Extension is seeking experienced professionals to serve as Part-Time Instructors for courses within our Data Science and Data Engineering certificate programs. This role requires in-person instruction at our Westwood or Downtown Los Angeles (DTLA) campuses. We are looking for passionate subject matter experts who can translate complex, real-world data challenges into an engaging and effective learning experience for adult students.

The current opening is for our Data Science & Data Analytics courses. Qualified applicants possessing current knowledge and teaching experience in this area are encouraged to apply.

Applications to teach are accepted throughout the year to fill immediate program needs and to increase the depth of the instructor pool. We are looking for instructors to teach the following courses: • Data Science Fundamentals • Data Engineering • Big Data Management • Machine Learning System Design • Python Programming • Cloud Computing • Exploratory Data Analysis and Visualization • Data Modeling and Datastore Design • Data Pipeline Architecture

The primary responsibilities of the instructor are to ensure a high-quality, engaging, and relevant educational experience for students.

Curriculum Development:

• Develop and/or update existing course syllabus in consultation with the UCLA Extension Program Director using the approved syllabus template.

Course Delivery & Preparation:

• Prepare course materials (e.g., lectures, readings, assignments) and learning assessments (quizzes, projects) in the learning management system, Canvas.
• Clearly communicate and teach the course objectives and the specific learning outcomes to students. Student Engagement & Support:
• For 100% online instructional mode, hold once a week online office hours via Zoom for students to optionally participate to cover course-related topics and Q/A.
• Maintain weekly, and preferably daily, interaction with students' discussion posts on Canvas to promote high engagement and collaboration for an optimum learning experience.
• Respond to student questions and learning needs in a timely manner.

Assessment & Grading:

• Review students' progress through the course and assign timely grading of all coursework.
• Enter final letter grades in the required portal at the end of each academic quarter.

Employment as a UCLA Extension Instructor is dictated by contract terms and conditions. Please take the time to read the UCLA Extension Instructor Employment Policies

For information on UCLA Extension instructor benefits, please visit Pay, Benefits, & Privileges.

Basic qualifications: Education: A minimum of a master's degree in Data Science, Computer Science, Statistics, or a closely related quantitative field. Experience: A minimum of 10 years of recent, practical, professional experience working as a Data Scientist, Data Engineer, or in a similar advanced analytics role.

Technical Expertise (Must be proficient in at least two areas): Data Science: Machine learning (e.g., Python/R, scikit-learn, TensorFlow, PyTorch), statistical modeling, and data visualization. Data Engineering: Cloud data platforms (e.g., AWS, Azure, GCP), ETL/ELT pipeline design, distributed processing (e.g., Spark, Hadoop), and advanced SQL/NoSQL databases. Teaching/Training: Prior teaching or training experience with adult learners in a corporate or academic setting is highly desirable.

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.