Applied Data Science- Special Session Lecturer Pool

Department Summary

The Department of Applied Data Science offers academic programs to address the emerging workforce demands of interdisciplinary talents who design and deploy intelligent solutions to real-world data challenges. Students acquire a comprehensive understanding and knowledge of the principles, methodologies, and technologies of data science. Silicon Valley is known for its leadership in the big data economy and its demand for talent in response to the exponential growth of data. The department continuously seeks guidance from leading data professionals and companies to ensure that the curriculum is relevant for growing the talent needed in Silicon Valley.

Local data professionals regularly interact with our students through teaching classes, speaking at seminars, sponsoring internships, and supervising capstone projects. Faculty members actively engage with industry partners and sponsors to assess our curricula and update learning objectives to provide the most up-to-date skills for supporting innovations in this region.

The department is an academic hub, in partnership with other SJSU departments and industry partners, for promoting education and research in applied data science. To address the immense demand for data science professionals, the department launched an MS in Data Analytics program in August 2018. This program provides students with the advanced education necessary to draw insights from real data and apply analytical skills to solve practical problems. Currently, 200 students are enrolled in the program, with continued plans for future growth.

Brief Description of Duties

• Lecturers are expected to teach their courses effectively; to maintain appropriate office hours in accordance with University Policy; and to cooperate with the department in the peer-review process.
• The candidate must demonstrate awareness and experience understanding the needs of a student population of great diversity – in age, abilities, cultural background, ethnicity, religion, economic background, primary language, sexual orientation, gender identity, and academic preparation – through inclusive course materials, teaching strategies and advisement.
• Faculty shall organize all their classes within the Canvas Learning Management System (LMS).
• All classes must be offered and meet as scheduled throughout the entire semester or term, in the mode assigned and listed in the schedule of classes (i.e., asynchronous, synchronous, bichronous, in-person, or hybrid).

Required Qualifications

• A Ph.D. or Master’s degree with at least 5 years of significant and relevant professional experience in a STEM field is required.
• Knowledge of the subject matter of the discipline in Data Science and Analytics.
• Evidence of satisfactory achievement in previous academic work.
• Applicants should demonstrate an awareness of and sensitivity to the educational goals of a multicultural population as might have been gained in cross-cultural study, training, teaching and other comparable experience.