Chief Academic officer

AI Startup company

Chief Academic officer

People Impact

Company

Home

Chief Academic officer

at AI Startup company

Agency job

via People Impact

8 - 20 yrs

₹15L - ₹30L / yr

Bengaluru (Bangalore)

Skills

doctoral

Data Science

Mathematics

Teaching

Curriculum Development: Collaborate with Academic Advisory Committee and Marketing team members to design and develop comprehensive curriculum for data science programs at undergraduate and graduate levels. Ensure alignment with industry trends, emerging technologies, and best practices in data science education.
Faculty Recruitment and Development: Lead the recruitment, selection, and development of faculty members with expertise in data science. Provide mentorship, support, and professional development opportunities to faculty to enhance teaching effectiveness and academic performance.
Quality Assurance: Establish and maintain robust mechanisms for quality assurance and academic oversight. Implement assessment strategies, evaluation criteria, and continuous improvement processes to ensure the delivery of high-quality education and student outcomes.
Student Engagement: Foster a culture of student engagement, innovation, and success. Develop initiatives to support student learning, retention, and career readiness in the field of data science. Provide academic counselling and support services to students as needed.
Industry Collaboration: Collaborate with industry partners, employers, and professional organizations to enhance experiential learning opportunities, internships, and job placement prospects for students. Organize industry events, guest lectures, and networking opportunities to facilitate knowledge exchange and industry engagement.
Research and Innovation: Encourage research and innovation in data science education. Facilitate faculty research projects, interdisciplinary collaborations, and scholarly activities to advance knowledge and contribute to the academic community.

Budget Management: Develop and manage the academic budget in collaboration with the finance department. Ensure efficient allocation of resources to support academic programs, faculty development, and student services.

Curriculum Development: Collaborate with Academic Advisory Committee and Marketing team members to design and develop comprehensive curriculum for data science programs at undergraduate and graduate levels. Ensure alignment with industry trends, emerging technologies, and best practices in data science education.
Faculty Recruitment and Development: Lead the recruitment, selection, and development of faculty members with expertise in data science. Provide mentorship, support, and professional development opportunities to faculty to enhance teaching effectiveness and academic performance.
Quality Assurance: Establish and maintain robust mechanisms for quality assurance and academic oversight. Implement assessment strategies, evaluation criteria, and continuous improvement processes to ensure the delivery of high-quality education and student outcomes.
Student Engagement: Foster a culture of student engagement, innovation, and success. Develop initiatives to support student learning, retention, and career readiness in the field of data science. Provide academic counselling and support services to students as needed.
Industry Collaboration: Collaborate with industry partners, employers, and professional organizations to enhance experiential learning opportunities, internships, and job placement prospects for students. Organize industry events, guest lectures, and networking opportunities to facilitate knowledge exchange and industry engagement.
Research and Innovation: Encourage research and innovation in data science education. Facilitate faculty research projects, interdisciplinary collaborations, and scholarly activities to advance knowledge and contribute to the academic community.

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