Key Responsibilities Curriculum Development Collaborate with the Academic Advisory Committee and Marketing team to design and develop comprehensive data science curricula for both undergraduate and graduate programs. Ensure that the curriculum reflects current industry trends, emerging technologies, and educational best practices. Faculty Recruitment and Development Lead the recruitment, selection, and ongoing development of faculty members with expertise in data science. Provide mentorship and professional development opportunities to strengthen teaching effectiveness and academic outcomes. Quality Assurance Implement and oversee robust academic quality assurance processes. Establish evaluation frameworks, assessment methodologies, and continuous improvement mechanisms to maintain high standards of teaching and student success. Student Engagement Cultivate an environment that encourages student engagement, innovation, and achievement. Develop strategies to support student learning, retention, and career development. Offer academic advising and support services as needed. Industry Collaboration Build and maintain partnerships with industry leaders, employers, and professional organizations. Create experiential learning opportunities through internships, guest lectures, and networking events to bridge academia and industry. Research and Innovation Promote a culture of research and innovation in data science education. Facilitate faculty-led research initiatives, interdisciplinary collaborations, and scholarly contributions to enhance the institution's academic standing. Budget Management Work in partnership with the finance department to develop and manage the academic budget. Ensure effective resource allocation to support program delivery, faculty initiatives, and student services. Skills & Competencies - Deep expertise in data science across research, teaching, and industry interaction - Proven leadership in academic administration, curriculum development, and faculty oversight - Strong interpersonal, communication, and leadership capabilities - Ability to work collaboratively with faculty, students, administrative staff, and external stakeholders - Commitment to academic innovation and continuous improvement - Familiarity with the EdTech landscape and online learning methodologies - Proficiency in Learning Management Systems (LMS) and educational technology - Programming skills in Python, R, and SQL - Hands-on experience with tools like TensorFlow, PyTorch, and scikit-learn - Expertise in event coordination, project management, and problem-solving
