Tutor - Data Analytics

4 weeks ago

Hyderabad, India Coursevita Full time

Join Coursevita, an innovative EdTech company dedicated to global education transformation. We're hiring a seasoned Data Analysis Tutor to empower learners. In this role, you'll deliver comprehensive instruction and support, helping students excel in our Data Analyst courses.

Roles and Responsibilities:

  1. Conduct live online tutoring sessions for learners enrolled in Data Analyst courses, covering fundamental concepts, techniques, and tools in data analysis.

  2. Develop and deliver engaging and interactive lesson plans, tutorials, and assignments tailored to the learning objectives and skill levels of learners.

  3. Provide personalized guidance, feedback, and support to learners to help them understand data analysis methodologies, algorithms, and best practices.

  4. Facilitate discussions, group projects, and hands-on activities to reinforce learning and promote critical thinking and problem-solving skills among learners.

  5. Stay updated on the latest trends, advancements, and best practices in data analysis, data visualization, and statistical modelling.

  6. Assist in the development and enhancement of course content, curriculum, and learning resources based on learner feedback and industry trends.

  7. Collaborate with other tutors, subject matter experts, and instructional designers to ensure the quality and effectiveness of Data Analyst courses.

  8. Foster a positive and inclusive learning environment that encourages active participation, collaboration, and continuous improvement among learners.

  9. Provide support and guidance to learners outside of scheduled tutoring sessions through email, discussion forums, and virtual office hours.

  10. Maintain accurate records of tutoring sessions, learner progress, and performance evaluations in the company's learning management system.



Requirements
  1. Strong understanding of core concepts and principles of data analysis, including data manipulation, exploratory data analysis, and statistical inference.
  2. Proficiency in data analysis tools and software, such as Excel, R, Python (with libraries like pandas and NumPy), or SQL.
  3. Experience with data visualization techniques and tools, such as Tableau, Power BI, or matplotlib/seaborn.
  4. Knowledge of statistical methods and techniques commonly used in data analysis, such as regression analysis, hypothesis testing, and clustering.
  5. Ability to explain complex data analysis concepts, methodologies, and techniques in a clear and understandable manner.
  6. Experience applying data analysis concepts to real-world datasets and problems, including data cleaning, transformation, and interpretation.
  7. Familiarity with best practices in data ethics, privacy, and security is a plus.


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