Data Science Trainer

The Data Science Trainer will design, develop, and deliver educational programs to teach data science concepts, tools, and techniques to learners (could be students, working professionals, internal teams). They should be able to bridge theory and practice, provide hands-on experience, mentor learners, and ensure that trainees are job-ready or able to apply skills in real-world projects.

• Design and develop training curriculum, modules, lesson plans, and supporting materials (presentations, assignments, case studies, workshops) in data science topics.
• Deliver training sessions (online / classroom / hybrid) covering fundamentals and advanced topics such as: Python / R programming Statistics & probability Data manipulation, cleaning, wrangling (Pandas, NumPy etc.) Data visualization (Matplotlib, Seaborn, Tableau, Power BI) Machine Learning (supervised, unsupervised, model evaluation, etc.) Deep Learning / AI frameworks (TensorFlow, Keras, PyTorch) as appropriate Big Data tools or distributed computing (Spark, Hadoop) if relevant
• Develop hands-on labs / projects / case studies so that learners can apply concepts practically.
• Assess learner progress through quizzes, assignments, projects; give constructive feedback.
• Mentor students, provide guidance in career preparation e.g., resume building, interview prep, project reviews.
• Stay up-to-date with industry trends, emerging tools, libraries, and techniques; update curriculum accordingly.
• Collaborate with content, pedagogy, technical teams to ensure quality and relevance.
• Evaluate training effectiveness via feedback, performance metrics; continually improve delivery and content.
• (Optional) Host webinars, workshops, guest lectures. Participate in marketing or outreach for training programs.