• Deliver engaging, practical sessions on R programming, business statistics, and data analysis fundamentals, progressing to applied use cases and real-world project work.
• Guide learners through statistical concepts and R programming using RStudio, with emphasis on regression analysis, hypothesis testing, and predictive analytics applied to business problems.
• Mentor students through real-world analysis projects—from problem definition and methodology selection to translating findings into actionable business recommendations.
• Evaluate student understanding through hands-on exercises, assignments, quizzes, and capstone project presentations.
• Support learners with R programming challenges, statistical interpretation, and translating technical findings into business language and insights.
• Collaborate with the curriculum team to deliver consistent, high-quality instruction aligned with industry expectations and business applications.

Advanced proficiency in R programming and RStudio with demonstrated experience in statistical modeling (regression analysis, hypothesis testing, forecasting) Strong expertise in business statistics, including descriptive analytics, inferential statistics, and predictive modeling techniques Practical experience in Power BI for data visualization and dashboarding (secondary skill) Demonstrated ability to explain complex statistical concepts and data techniques clearly to diverse, non-technical audiences Strong communication skills with ability to translate technical findings into actionable business insights and recommendations Prior experience in training, teaching, or mentoring others in statistics or data analysis is preferred Bachelor's degree (or higher) in Statistics, Data Science, Mathematics, Economics, Business Analytics, or a related field Portfolio or examples of past data analyses, projects, or business case studies available for review