Data Analyst Offline Trainer

Key Responsibilities:

• Training Delivery:
• Conduct live and recorded online sessions for learners, covering fundamental and advanced data analysis topics. Ensure the content is engaging, clear, and interactive. Topics may include:
• Data collection and cleaning
• Data visualization and reporting
• Statistical analysis and hypothesis testing
• SQL querying and database management
• Introduction to Python/R for data analysis
• Data modeling and analysis using tools like Excel, Power BI, or Tableau
• Course Design & Curriculum Development:
• Collaborate with the content development team to create, update, and refine course materials, including presentations, exercises, and assessments. Ensure the curriculum aligns with current industry standards and best practices.
• Student Support and Engagement:
• Provide guidance and support to students during and after training sessions. Answer questions, review assignments, and offer constructive feedback. Foster a supportive and collaborative learning environment through online platforms.
• Assessments and Progress Tracking:
• Design quizzes, tests, and assignments to evaluate students' understanding and progress. Track learner performance and provide additional support for students who may be struggling.
• Mentorship & Coaching:
• Offer mentorship to students by providing career guidance, tips for the job market, and advice on building a strong data analysis portfolio.
• Continuous Improvement:
• Stay up-to-date with the latest tools, techniques, and industry trends in data analytics. Regularly update course content to reflect new developments and ensure that training materials are relevant and accurate.
• Marketing and Promotion (Optional):
• Assist with promotional activities to attract new learners. Share success stories, testimonials, and your expertise on various platforms to increase course visibility.

Qualifications:

• Experience:
• Minimum of 4-8 years of experience working as a data analyst or in a similar data-related role.
• Prior experience in teaching, tutoring, or training (especially online training) is highly preferred.
• Technical Skills:
• Proficiency in data analysis tools and technologies, including:
• Excel (advanced)
• SQL (queries, joins, aggregations)
• Python or R for data manipulation and analysis
• Data visualization tools (e.g., Tableau, Power BI)
• Statistical techniques (e.g., regression, hypothesis testing)
• Familiarity with data cleaning techniques, data wrangling, and ETL processes.