Job description
Summit Valley University invites applications for a full-time Lecturer in Data Science to join our growing Department of Computer Science and Statistics. The successful candidate will deliver engaging, accessible instruction across undergraduate and graduate courses, contribute to curriculum development, and support a vibrant research community in data science.
We seek an innovative educator with a commitment to inclusive teaching practices, student mentorship, and collaborative scholarship. This role offers opportunities to design new courses, develop hands-on labs, and engage with industry partners to ensure programs remain current and industry-relevant.
Location: Cambridge, Massachusetts. Compensation is competitive and commensurate with experience. This position is eligible for university benefits and funding for professional development.
Responsibility
- Deliver high-quality lectures and seminars for undergraduate and graduate Data Science courses, with emphasis on practical, project-based learning.
- Design, update, and assess curricula to align with evolving data science practices and accreditation standards.
- Direct capstone projects and supervise student research, providing guidance on methodology, analysis, and reporting.
- Advise students, maintain regular office hours, and support a diverse and inclusive learning environment.
- Collaborate with faculty on program development, assessment, and cross-disciplinary initiatives.
- Engage with industry partners to integrate real-world data sets, case studies, and internships into coursework.
- Participate in service to the department, university committees, and professional communities; contribute to grant writing and scholarly activities as feasible.
Qualification
- PhD in Data Science, Computer Science, Statistics, or a closely related field; or a relevant Master’s degree with substantial professional experience and demonstrated teaching excellence.
- Demonstrated experience teaching at university level and designing data science or related courses.
- Strong proficiency in Python and libraries (pandas, scikit-learn), R, SQL; familiarity with big data tools and ML workflows.
- Excellent communication, presentation, and mentoring skills; ability to work with diverse student populations.
- Commitment to inclusive pedagogy, equity, and student success; experience with curriculum development and assessment.
- Ability to collaborate across departments and contribute to research or scholarly activities in data science or related fields.
- U.S. work authorization or visa sponsorship as applicable; willingness to support program growth and student outcomes.