Computer Science Department Head

2 weeks ago


New York, United States The Packer Collegiate Institute Full time

The Computer Science Department Head leads a Lower through Upper School program that prepares students to understand computing, data, and AI. The department head guides curriculum design, instruction, and long term planning in ways that reflect current research in the field. The goal is a program where all students engage in meaningful computer science learning and see themselves as contributors and problem solvers. Start Date: August 24, 2026 Key Responsibilities Serve as an instructional leader on the Academic Council team. Communicate the department’s philosophy, goals, and student pathways with clarity across all divisions. Lead curriculum and program development from First through grade 12. Build a curriculum that supports student ownership of learning using key skills and standards. Design experiences that teach research, evaluation of information, and original creation. Supports teaching that respects student identity, affirms diverse experiences, and responds to the cultural and social context in which students learn. Strengthen design thinking and problem solving skills through purposeful tasks. Integrate computational thinking across grade levels. Teach students to communicate ideas through code, data, writing, and multimedia. Build collaborative learning structures. Embed digital responsibility, data awareness, and ethical use of AI across the program. Maintain a clear sequence of courses from foundations through advanced study. Support faculty growth through observations, feedback, guidance, and action steps. Oversee course offerings, review placement processes, and develop advanced pathways. Manage departmental budget with the Director of Academic Technology planning for instruction, hardware, software, and professional learning. Lead hiring for computer science faculty in partnership with division leaders and the Academic Dean. Plan and lead department meetings, set goals, and track progress. Support new faculty with orientation to curriculum and department expectations. Teach two classes and model strong teaching practice grounded in research. Carry out responsibilities assigned by the Director of Academic Technology or Academic Dean. Qualifications Minimum of five years of experience teaching computer science. Strong knowledge of programming, computational thinking, data science, and current work in AI. Experience designing Lower through Upper School learning progressions in computing. Record of strong, innovative teaching practice. Strong communication skills with students, families, faculty, and colleagues. Ability to lead change and support colleagues through shifts in practice. Advanced degree in computer science, computer science education or a related field preferred. Reasonable Accommodations: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable Accommodations may be made to enable qualified individuals with disabilities to perform the essential functions. Packer's values and vision of educational excellence include embracing diversity, fostering community, nurturing a sense of belonging, and ensuring all learners are valued and challenged. We actively embrace the diversity of New York City and seek employees who share Packer’s values of equity, inclusion, and belonging, and who wish to learn from the experiences and perspectives of others. We strongly encourage applications from candidates whose backgrounds and perspectives may be underrepresented. The Packer Collegiate Institute does not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national and ethnic origin, ancestry, age, marital status, disability, or any other characteristic protected by law. This policy applies to, but is not limited to, educational policies, admission, financial aid, hiring and employment practices, use of school facilities, athletics, and other school-administered programs. Salaries are determined based on a scale reflecting years of teaching experience and level of education. #J-18808-Ljbffr


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