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Lecturer - Data Science - School of Information

Position overview

Position title: Lecturer
Salary range: The starting, full-time equivalent annual salary rate is currently $134,777. Appointments are typically from one to three sections per term for up to three terms per year, resulting in the total compensation of approximately $7,637 per section at 17% FTE over each academic term, as of Spring 2025. This salary rate will increase in subsequent terms in accordance with the terms of the labor contract.

Percent time: Percent time 10% to 100% time

Anticipated start: Positions typically start in January, May, and August.

Review timeline: Applicants are considered for positions as needs arise; the existence of this pool does not guarantee that a position is available.

Position duration: Initial position duration is for up to one year, with possibility for renewal. Appointments may be renewed based on need, funding, and performance.

Application Window
Open date: February 25, 2025

Next review date: Tuesday, Mar 11, 2025 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.

Final date: Wednesday, Feb 25, 2026 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Position description

The School of Information at the University of California, Berkeley, invites applications for a pool of part-time, non-tenure track lecturers to teach online courses in the Master of Information and Data Science (MIDS) program. We seek exceptional instructors with professional and/or academic expertise who can lead small, highly interactive sections of around 15 graduate students in this innovative, online program.

Courses in the MIDS program are pre-designed and structured, allowing instructors to focus on delivering dynamic and engaging learning experiences while providing valuable expertise to enhance student outcomes. Screening of applicants is ongoing and will continue as the needs of the program evolve. The number of available positions may vary by semester based on the School's requirements.

Please Note:

• Applicants must be based in the United States to be eligible for this position.


• No funding is available for visa sponsorship or relocation expenses due to budget constraints.

About The I School
The Berkeley School of Information (I School) is a global bellwether in a world awash in information and data, boldly leading the way with education and fundamental research that translates into new knowledge, practices, policies, and solutions. I School scholars and practitioners thrive in the intersections where people, organizations, and societies interact with information, technology, and data. Faculty comprise a mix of disciplines, including information, computer science, economics, political science, law, sociology, design, media studies, and more.

The I School offers three professional master's degrees and an academic doctoral degree. The MIMS program trains students for careers as information professionals and emphasizes small classes and project-based learning. The MIDS program trains data scientists to manage and analyze the coming onslaught of big data, in a unique high-touch online degree. The MICS program prepares cybersecurity leaders with the technical skills and contextual knowledge necessary to develop solutions for complex cybersecurity challenges. The Ph.D. program equips scholars to develop solutions and shape policies that influence how people seek, use, and share information. Our cohorts and classes are small enough to support intense student engagement; and we encourage collaboration among the students, faculty, and staff in the I School community. Our alumni have careers in diverse fields, such as data science, user experience design and research, product management, engineering, information policy, cybersecurity, and more.

We are committed to attracting outstanding instructors from academia and industry who bring diverse perspectives and experiences to the virtual classroom. Whether your expertise lies in groundbreaking research, innovative industry applications, or both, we value professionals who can bridge theory and practice. Successful lecturers inspire graduate students by integrating real-world applications with deeper theoretical exploration, fostering critical discussions of historical and emerging trends, and preparing students to make an impact in the rapidly evolving field of data science.

If you are an enthusiastic educator or practitioner passionate about shaping the next generation of data science leaders, we encourage you to join our exceptional instructional team.

The instructor role is an exciting opportunity to contribute to the success of graduate students in cutting-edge online MIDS master's programs at UC Berkeley's School of Information.

Responsibilities Include:
Delivering Engaging Online Classes: Plan and lead synchronous online sessions focusing on active learning. Facilitate meaningful discussions, collaborative group activities, and practical exercises that enhance students' understanding and application of core concepts.

Facilitating Student-Centered Learning: Provide personalized support to students by holding virtual office hours, moderating online discussions, and leveraging student analytics to identify and support individual learning needs.

Designing and Refining Course Materials: Collaborate with course teams to prepare and update instructional materials. Ensure all materials align with program objectives and DEIBJ principles.

Providing Constructive Feedback: Deliver timely, actionable feedback on student assignments and projects to promote growth and mastery of key competencies.

Maintaining Course Operations: Use the learning management system (LMS) and other educational technology tools to manage course websites, post assignments, and communicate with students effectively.

Collaborating with Faculty Teams: Actively participate in course meetings to align instructional practices, address challenges, and share innovative teaching strategies. Attend monthly or bi-monthly faculty meetings to stay connected with program goals, initiatives, and effective online teaching pedagogy.

Promoting Diversity and Inclusion: Foster an inclusive, equitable learning environment that respects diverse perspectives and supports all students in achieving their academic and professional goals.

Please note:

The use of a lecturer pool does not guarantee that an open position exists. See the review date in AP Recruit to learn whether the school is reviewing applications for a specific position. If no future review date is specified, your application may not be considered at this time.

The School of Information is interested in candidates who will contribute to diversity and equal opportunity in higher education through their teaching or other related areas. We require that applicants submit a statement addressing past and/or potential contributions.

UC Berkeley has several policies and programs to support all employees as they balance work and family.

Program: http://datascience.berkeley.edu

Policies and Programs to Support All Employees: https://ofew.berkeley.edu/support-faculty/family-responsive-policies-benefits-programs-and-resources

Course Descriptions: https://www.ischool.berkeley.edu/courses/datasci

Qualifications
Basic qualifications (required at time of application)
A bachelor's degree (or equivalent international degree).

Additional qualifications (required at time of start)
Minimum 4 years professional experience in the relevant field.

Minimum 2 years experience in teaching in higher education or professional development in relevant fields. Professional development instructional activities would include leading workshops, executive education, corporate training, or industry-recognized certification programs.

Preferred qualifications
An advanced degree in Data Science, Information, Information Science, Statistics, Computer Science, Engineering, Political Science, Sociology, Law, Economics or related field.

10 + years of professional experience in fields such as Data Science, Information, Information Science, Statistics, Computer Science, Engineering, Political Science, Sociology, Law, Economics or related field.

Multiple years of demonstrated excellence in teaching college-level courses, including experience with online instruction.

Familiarity with and use of collaborative learning techniques and student-centered methods of instruction.

Proven organizational skills and ability to complete assignments timely and accurately with minimal supervision.

Possess excellent communication skills, both oral and written, and the ability to communicate effectively with students with a wide range of skills.

Possess excellent interpersonal, customer service, and problem-solving skills. Ability to work well with students, faculty, and staff. Demonstrated strength or potential in teaching at the college level.

Demonstrated ability to support the academic, professional, and personal development of a diverse community while advancing diversity, equity, inclusion, belonging and justice (DEIBJ) in a multidisciplinary environment.

Teaching or in-depth knowledge and experience in at least one of the following core areas (please see course descriptions):

• Applied Cloud Computing for Data Science


• Applied Machine Learning


• Applied Statistics(R)


• Capstone Projects - real world projects and industry collaboration


• Computer Vision


• Data Visualization and Communication


• Deep Learning and Neural Networks


• Edge and IoT Data Science


• Experiments and Causal Inference


• Fundamentals of Data Engineering


• Generative AI


• Introduction to Data Science Programming (Python)


• Leadership in Data-Driven Transformation


• Machine Learning at Scale


• Machine Learning Systems Engineering


• Natural Language Processing with Deep Learning


• Privacy, Security, and Ethics in Data Science


• Regression and Time Series Analysis


• Research Design and Data Analysis


• Scalable Data Mining and Analysis


• Statistical Methods for Discrete Response, Time Series, & Panel Data


• Special Topics such as: AI for Sustainability, Autonomous Systems and Robotics Data, Human-Centered Data Science, Spatial Data Science, Time-Series Analysis and Forecasting

Application Requirements

Document requirements

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


• Cover Letter


• Statement of Teaching Interests/Experience/Approach - Applicants must submit a brief statement outlining their teaching philosophy, experience, and methods. The statement should clearly describe the format, audience, and scope of teaching or professional development experience.
  
  The statement should highlight areas of expertise, instructional strategies for creating engaging and inclusive learning environments, and any experience with online or technology-enhanced teaching. Emphasis on connecting theory to practice and fostering student success is encouraged.
  
  Please indicate which class(es) you believe you are qualified to teach.


• Statement on Contributions to Diversity, Equity, Inclusion, Belonging, and Justice - Statement on your contributions to diversity, equity, inclusion, belonging, and justice in research, teaching, and service, including information about your record of activities to date, and plans for contributing if hired at UC Berkeley. More Information and guidelines.


• Teaching Evaluations, if available (Optional)

Reference requirements

• 3 required (contact information only)

Apply link: https://aprecruit.berkeley.edu/JPF04648

Help contact: alhintz@berkeley.edu

About UC Berkeley

UC Berkeley is committed to diversity, equity, inclusion, and belonging. The excellence of the institution requires an environment in which the diverse community of faculty, students, and staff are welcome and included. Successful candidates will demonstrate knowledge and skill related to ensuring equity and inclusion in the activities of their academic position (e.g., teaching, research, and service, as applicable).

The University of California, Berkeley 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.

Please refer to the University of California's Affirmative Action Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

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.

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


• UC Anti-Discrimination Policy for Employees, Students and Third Parties


• APM - 035: Affirmative Action and Nondiscrimination in Employment

Job location
Berkeley, CA, or remote (US-based).


To apply, visit https://aprecruit.berkeley.edu/JPF04648