Analyze Training Program Data : Collect, clean, and analyze data from various training programs to assess student performance, engagement, and satisfaction. Identify trends, patterns, and areas for improvement to enhance the learning experience.
Develop Data-Driven Insights : Use statistical analysis, machine learning, and data mining techniques to generate insights from training data and industry trends. Provide recommendations to improve course content, delivery methods, and student outcomes.
Monitor Industry Trends : Stay updated on industry trends in electric mobility, renewable energy, and related fields. Analyze external data sources to identify emerging skills and competencies required in the market, and use these insights to inform curriculum development.
Collaborate with Curriculum Developers and Instructors : Work closely with curriculum developers and instructors to integrate data-driven insights into course design and content. Provide feedback on educational materials based on data analysis.
Develop Predictive Models : Create predictive models to forecast student performance, identify at-risk learners, and suggest interventions to enhance retention and success rates. Use these models to inform strategic decisions related to course offerings and marketing.
Design and Conduct Experiments : Design and conduct A/B tests and other experiments to evaluate the effectiveness of different teaching methods, course formats, and content types. Analyze results to determine the most effective approaches for diverse learner groups.
Visualize Data and Present Findings : Create clear and compelling data visualizations to communicate insights and findings to stakeholders. Present results to senior management, instructors, and curriculum developers to drive data-informed decision-making.
Improve Data Collection and Management Processes : Work with IT and operations teams to enhance data collection, storage, and management processes. Ensure data integrity and accessibility for analysis and reporting.
Automate Reporting and Insights Generation : Develop and implement automated reporting tools and dashboards that provide real-time insights into program performance and learner engagement.
Contribute to Research and Development : Participate in research projects focused on educational technology and data analytics. Contribute to the development of new tools and methodologies that enhance data-driven decision-making in education.
Requirements
A bachelor s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. A master s degree or Ph.D. is preferred.
A minimum of 3-5 years of experience in data science, analytics, or a related field, preferably within the education or technology sectors.
Strong proficiency in programming languages such as Python, R, or SQL, and experience with data visualization tools such as Tableau, Power BI, or similar.
Expertise in statistical analysis, machine learning, data mining, and predictive modeling.
Proven experience in designing and conducting experiments and A/B tests.
Strong analytical and problem-solving skills, with the ability to interpret complex data and generate actionable insights.
Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical stakeholders.
Experience in developing automated reporting tools and dashboards.
Ability to work independently and manage multiple projects simultaneously.
Passion for education, technology, and the advancement of data-driven decision-making.
Self-motivated, proactive, and adaptable to a fast-paced educational environment.
Fluent in English; proficiency in additional languages is a plus