Data Science/Data Analytics trainer

As a Data Analytics Trainer, you will be responsible for delivering engaging and informative training on various data analytics concepts and tools. You will guide learners through the process of analyzing, visualizing, and interpreting data, ensuring they develop the skills necessary to make data-driven decisions. Preference will be given to candidates with Data Science experience, including knowledge of machine learning and advanced data analysis techniques.

Key Responsibilities:

Training Delivery: Conduct interactive training sessions on topics including data collection, cleaning, analysis, and visualization using tools like Excel, SQL, Python, R, Tableau, Power BI, etc.
Curriculum Development: Develop and update training materials and exercises that align with current industry trends and best practices.
Learner Support: Offer guidance, feedback, and mentorship to help learners master key concepts and apply them effectively in their careers.
Advanced Topics (Preferred): Provide optional or advanced training on machine learning, statistical modeling, and data science topics such as Python libraries (Pandas, NumPy, Scikit-learn) and TensorFlow.
Assessment and Evaluation: Design and administer quizzes, tests, and assignments to track learner progress and provide feedback for improvement.
Professional Development: Stay updated on the latest trends in data analytics and data science to improve your teaching and course content.
Collaboration: Work closely with the training team to ensure seamless course delivery and contribute to the development of new programs.
Qualifications:

Educational Background: Bachelor's or Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
Experience: 2+ years of experience in data analytics. Experience in teaching or training is highly preferred. Data Science experience is a bonus!
Technical Skills: Proficiency in tools such as Excel, SQL, Python, R, Tableau, Power BI, and machine learning libraries (e.g., Scikit-learn, TensorFlow).
Strong Communication Skills: Ability to explain complex technical concepts clearly and engage learners.
Teaching and Mentoring Skills: Strong presentation and mentoring abilities to help students understand and apply data analytics concepts.
Certifications (Preferred): Data analytics or data science certifications (e.g., Google Data Analytics, Microsoft Certified: Data Analyst Associate) are a plus.
Additional Preferred Skills:

Experience with advanced analytics tools (Hadoop, Spark) or cloud platforms (AWS, Google Cloud).
Ability to deliver both in-person and remote training.
Familiarity with business applications of data analytics in industries such as healthcare, finance, and marketing.