LEAD TRAINER DATA SCIENCE About the Institute of Data The Institute of Data is a Professional Network of Data Scientists, Cyber Security Analysts, Digital Marketers and Software Engineers. In partnership with leading universities in Australia, New Zealand & America, and the government of Singapore, we transform careers for a data-driven world through practical, industry-focused courses. About the role We are seeking a Lead Trainer to lead this transformative experience for our students. We offer courses outside of business hours in conjunction with several University partners throughout the Midwest and east coast. The next opportunity is: Starting August 18th, 2025 to November 7th - Monday to Friday from 9am CST to 1pm CST. This classroom will be fully remote. The content is provided and covers mathematics, statistics, programming, data analysis, machine learning and AI techniques, and how they are applied to businesses and government organizations. Assessment is in the form of labs and project work. Students graduating from the course are well-equipped to take on junior data analyst roles. Deliver curriculum and support students to enter the industry Provide students with meaningful and prompt feedback on their progress Guide students through the development of real-world projects that will showcase their abilities to hiring managers Facilitate a dynamic and collaborative classroom community Inspire students to persevere through the challenges of learning complex subjects. Work with and guide Assistant Trainer to provide support to students. About you Bachelor in Computer Science, Science, Mathematics or related degree Minimum 5 years of professional data science experience. Expert in SQL, Python, and related Python libraries (Pandas, NumPy). Domain expertise in statistics, mathematics, and probability. Ability to build and apply statistical models in python using machine learning libraries, such as scikit-learn and stats models. Deep understanding of statistical hypothesis testing and experimental design, data visualization techniques and tools (i.e. matplotlib, bokeh, etc.), and manipulation of large data sets. Demonstrate and explain the function of machine learning algorithms such as regularized regression, naive bayes, decision trees, ensemble methods, KNN, K-means clustering, and neural networks. Excellent verbal communication with the ability to express technical material in an accessible way Desire to help others learn and grow and be comfortable in a classroom environment.