Data Analyst

Role Overview: As a Data Analytics and Data Science Trainer, your primary responsibility will be to develop and deliver comprehensive training programs for professionals looking to enhance their skills in data analysis, statistical methods, and machine learning. Your role will involve leveraging your technical expertise and teaching abilities to create engaging learning experiences that simplify complex concepts into practical skills effectively. Key Responsibilities: - Design, develop, and deliver training courses covering various topics such as data analytics, statistics, data visualization, and machine learning - Create hands-on exercises, projects, and assessments to reinforce learning outcomes - Adapt training content and delivery methods to accommodate different learning styles and skill levels - Stay updated with emerging trends and technologies in data science and analytics - Evaluate training effectiveness based on participant feedback - Provide mentorship and guidance to learners beyond formal training sessions - Collaborate with subject matter experts to ensure technical accuracy of training materials - Develop supplementary learning resources like documentation, guides, and reference materials Qualification Required: - Hold a Bachelor's degree in Statistics, Computer Science, Mathematics, or related field; Master's degree preferred - Minimum of 3 years practical experience in data analytics, data science, or related field - Proven track record of developing and delivering technical training - Strong programming skills in Python or R, focusing on data analysis libraries - Experience with SQL, data visualization tools, and machine learning frameworks - Excellent communication and presentation skills - Knowledge of adult learning principles and instructional design techniques preferred - Experience with learning management systems and virtual training delivery platforms beneficial Additional Company Details: The company offers a competitive salary and benefits package, continuous professional development opportunities, a collaborative and innovative work environment, flexible work arrangements, and the chance to influence the data skills of future professionals. They value diversity of thought and experience, encouraging applications from candidates of all backgrounds passionate about data education.,