Job
Description
As a Teaching Assistant for the Data Analytics Offline Programs, your role will involve supporting learners in mastering foundational analytics and applying them in real-world projects. You will collaborate closely with instructors to conduct doubt-clearing sessions, guide hands-on activities, support project development, and create a dynamic, application-driven learning environment. Key Responsibilities: - Conduct regular doubt-clearing sessions on core topics such as Python, SQL, Excel, Statistics, and Data Visualization (Tableau, Power BI). - Organize structured hands-on exercises, data-centric case studies, and analysis challenges using real-world datasets. - Monitor learner progress, identify conceptual gaps, and provide personalized support across analytics topics. - Foster an engaging classroom environment by encouraging curiosity, experimentation, and collaboration. Sub-Goals: - Strengthen learners' understanding in data analysis and business problem-solving through practice-oriented sessions. - Help students build confidence in handling real-world data challenges using industry-standard tools. - Collaborate with instructors to assist learners in achieving milestones such as Exploratory Data Analysis (EDA), Dashboard Design, Business Case Studies, and End-to-End Analytics Projects. - Guide learners in developing a strong portfolio showcasing skills in data analysis, storytelling with data, and decision-making support. - Ensure students gain hands-on exposure to tools and techniques widely used in analytics roles. Sub-Goals: - Equip students with practical, in-demand skills for roles like Data Analyst and Business Analyst. - Bridge theoretical knowledge with practical implementation using SQL, Excel, Python, Tableau, and Power BI. - Maintain batch records, including attendance, learner progress, and project completion tracking. - Coordinate with academic and operation teams for seamless batch execution, scheduling expert sessions, and managing resource distribution. - Resolve day-to-day operational or technical issues hindering the learning process. - Collaborate in refining teaching methods continuously, integrating feedback for improved delivery of analytics concepts. Sub-Goals: - Ensure smooth logistics and academic execution across batches. - Actively contribute to enhancing curriculum effectiveness and learner engagement strategies. Required Qualifications and Skills: - Education: Bachelors degree in Computer Science, Engineering, Statistics, Economics, Business, or related field (or equivalent industry experience). - Technical Skills: Strong foundation in Python, SQL, Excel, Statistics, and data visualization (Tableau, Power BI). - Hands-on Experience: Working with real datasets, building dashboards, and performing end-to-end data analysis projects. - Communication: Ability to explain analytical concepts clearly and engagingly. - Mentorship: Passion for teaching and mentoring learners at various data journey stages. - Collaboration & Time Management: Balancing academic guidance, operational tasks, and team collaboration effectively. Preferred Qualifications: - Prior experience in mentoring learners or professionals in analytics fields. - Project or teaching experience in business analytics, visualization, or applied data projects. - Familiarity with collaborative coding (Git/GitHub), cloud-based notebooks (Google Colab), and business reporting practices. - Participation in case competitions, hackathons, or publication of projects on platforms like Kaggle or GitHub. As a Teaching Assistant for the Data Analytics Offline Programs, your role will involve supporting learners in mastering foundational analytics and applying them in real-world projects. You will collaborate closely with instructors to conduct doubt-clearing sessions, guide hands-on activities, support project development, and create a dynamic, application-driven learning environment. Key Responsibilities: - Conduct regular doubt-clearing sessions on core topics such as Python, SQL, Excel, Statistics, and Data Visualization (Tableau, Power BI). - Organize structured hands-on exercises, data-centric case studies, and analysis challenges using real-world datasets. - Monitor learner progress, identify conceptual gaps, and provide personalized support across analytics topics. - Foster an engaging classroom environment by encouraging curiosity, experimentation, and collaboration. Sub-Goals: - Strengthen learners' understanding in data analysis and business problem-solving through practice-oriented sessions. - Help students build confidence in handling real-world data challenges using industry-standard tools. - Collaborate with instructors to assist learners in achieving milestones such as Exploratory Data Analysis (EDA), Dashboard Design, Business Case Studies, and End-to-End Analytics Projects. - Guide learners in developing a strong portfolio showcasing skills in data analysis, storytelling with data, and decision-making s
