Chief Academic Officer

Role & responsibilities

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

Job Specification

Knowledge / Education

Specific Skills

Desirable Experience

Ph D / Doctoral degree in Statistics, Computer science, Data science, Mathematics or related field

• Proven expertise and significant experience in data science, including research, teaching, and industry engagement.
• Previous leadership experience in academic administration, curriculum development, and faculty management.
• Strong interpersonal, communication, and leadership skills.
• Demonstrated ability to collaborate effectively with diverse stakeholders, including faculty, students, staff, and industry partners.
• Commitment to academic excellence, innovation, and continuous improvement in data science education.
• Familiarity with edtech industry and Online learning
• IT Savvy specific to Learning Management System
• Teaching and facilitation skills
• Proficiency in programming languages commonly used in data science, such as Python, R, or SQL.

Job Interface/Relationships:

Internal

External

• Management
• Faculty in different areas
• Students
• Departments: Academics, Digital transformation, Marketing & branding, IT, Finance, Operations
• Vendors
• Service providers
• Strategy consultants
• Educational Institutions / Universities
• Industry Leaders

Key Responsibilities

% Time Spent

1. Course delivery & Curriculum design & development 20%

2. Student onboarding, facilitation, engagement & support, evaluation, success and placement

40%

3. Quality assurance, student feedback and satisfaction, professional ethics and integrity in conduct 40%

Preferred candidate profile

Must have filed patents in AI