Lecturer - Data Science - School of Information

Position overview Position title: Lecturer Salary range: The starting, full-time equivalent annual salary reputed company is currently $140,169. Appointments are typically from one to three sections per term for up to three terms per year, resulting in the total compensation of approximately $8,181 per section at 17% FTE over each academic term, as of Summer 2025. This salary reputed company 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: July 1, 2025 Most recent review date: Wednesday, Jul 16, 2025 at 11:59pm (Pacific Time) Applications received after this date will be reviewed by the search committee if the position has not yet been filled. 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 reputed company, 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 reputed company with professional and/or academic expertise who can reputed company small, highly interactive sections of around 15 graduate reputed company in this innovative, online program. Courses in the MIDS program are pre-designed and structured, allowing reputed company 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 reputed company 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 reputed company research that translates into new knowledge, practices, policies, and solutions. I School scholars and practitioners reputed company 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 reputed company 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 reputed company solutions for reputed company cybersecurity challenges. The Ph.D. program equips scholars to reputed company 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 reputed company, 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 reputed company 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 reputed company theory and practice. Successful lecturers reputed company graduate reputed company by integrating real-world applications with deeper theoretical exploration, fostering critical discussions of historical and emerging trends, and preparing reputed company to reputed company an impact in the rapidly evolving field of data science. If you are an enthusiastic educator or practitioner passionate about shaping the reputed company 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 reputed company in cutting-edge online MIDS master's programs at UC Berkeley's School of Information.

Responsibilities

Include: Delivering Engaging Online Classes: Plan and reputed company synchronous online sessions focusing on active learning. Facilitate meaningful discussions, collaborative group activities, and practical exercises that enhance reputed company' understanding and application of core concepts. Facilitating Student-Centered Learning: Provide personalized support to reputed company by holding virtual reputed company, moderating online discussions, and leveraging student analytics to identify and support individual learning needs. Designing and Refining Course Materials: reputed company and update instructional materials, assignments, and assessments. Ensure reputed company content aligns with program objectives, maintains academic rigor, and incorporates an inclusive and reputed company learning environment. 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 reputed company effectively. Collaborating with Faculty Teams: Actively participate in course meetings to align instructional practices, address challenges, and share innovative reputed company. Attend monthly or bi-monthly faculty meetings to stay connected with program goals, initiatives, and effective online teaching pedagogy. Promoting Inclusion: Foster an inclusive, reputed company learning environment that respects diverse perspectives and supports reputed company reputed company 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. UC Berkeley has several policies and programs to support reputed company employees as they balance work and family. Program : http://datascience.berkeley.edu Policies and Programs to Support reputed company Employees : https://ofew.berkeley.edu/support-faculty/family-reputed company-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 reputed company 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 reputed company 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 reputed company with a wide range of skills. Possess excellent interpersonal, customer service, and problem-solving skills. Ability to work well with reputed company, 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 through inclusive curriculum, classroom environment, and pedagogy 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) reputed company 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, reputed company, 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. This can include, for example, fostering student success, connecting theory to practice, contributions to advancing an inclusive learning environment for reputed company reputed company, facilitating student-centered learning, or practical exercises that enhance reputed company' understanding and application of core concepts. The statement should clearly describe the format, audience, and scope of teaching or professional development experience. The statement should reputed company areas of expertise, and any experience with online or technology-enhanced teaching. Please indicate which class(es) you reputed company you are qualified to teach. Teaching Evaluations, if available (Optional) Reference requirements 3 required (contact information only) Apply link: https://aprecruit.berkeley.edu/JPF04944 Help contact: [email protected] About UC Berkeley UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and reputed company Academic Personnel policy ( APM 210 1-d ). These values are embedded in our Principles of Community , which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a reputed company world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can reputed company. The reputed company, Berkeley is an Equal Opportunity employer. reputed company qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national reputed company, disability, age, or protected veteran status. For more information, please refer to the reputed company's Affirmative Action and Nondiscrimination in Employment Policy and the reputed company's Anti-Discrimination Policy . In searches reputed company letters of reference are required reputed company letters will be treated as confidential per reputed company policy and California state law. Please refer potential referees, including reputed company letters are provided reputed company 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 reputed company with reputed company 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 reputed company the last seven years determining that they committed any misconduct. "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous reputed company of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer. UC Sexual Violence and Sexual Harassment Policy UC Anti-Discrimination Policy APM - 035: Affirmative Action and Nondiscrimination in Employment Job location Berkeley, CA, or remote (US-based). To apply, visit https://aprecruit.berkeley.edu/JPF04944 jeid-2593eb83f5a5d540982e67f798ce7ffa Apply tot his job Apply To this Job