Roles and Responsibilities1. Training & Instruction
- Deliver professional training in Data Science concepts, tools, and technologies.
- Teach subjects including:
- Python Programming for Data Science
- Data Analysis and Data Visualization
- Statistics and Probability
- Machine Learning Fundamentals
- Supervised and Unsupervised Learning
- Deep Learning Basics
- Data Preprocessing and Feature Engineering
- Model Evaluation Techniques
- Conduct both theoretical sessions and practical hands-on training.
2. Software & Tools Training
Train students in industry-standard tools and platforms such as:
- Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn)
- Jupyter Notebook / Google Colab
- SQL and Database Management
- Excel for Data Analysis
- Power BI / Tableau for Data Visualization
- Basic AI tools and frameworks (if applicable)
3. Curriculum Delivery
- Follow the institute’s approved syllabus and academic structure.
- Prepare lesson plans, coding exercises, assignments, and practical activities.
- Update course materials according to the latest industry trends and technologies.
- Simplify complex data science concepts for students with different learning abilities.
4. Practical Projects & Portfolio Development
- Guide students in developing real-world projects such as:
- Predictive analytics models
- Customer segmentation projects
- Sales and business analysis dashboards
- Recommendation systems
- Data-driven decision-making applications
- Help students create strong portfolios and project documentation.
5. Student Assessment & Evaluation
- Conduct coding tests, quizzes, assignments, and project evaluations.
- Monitor student progress and provide constructive feedback.
- Identify students who need additional support and provide mentoring.
6. Career & Placement Support
- Prepare students for job roles such as:
- Data Analyst
- Data Scientist
- Machine Learning Associate
- Business Intelligence Analyst
- Support students with:
- Resume preparation
- Portfolio development
- LinkedIn profile enhancement
- Mock technical interviews and aptitude preparation
7. Lab & Technical Support
- Ensure systems and training environments are properly configured with required tools.
- Assist students in setting up Python environments, Jupyter Notebook, databases, and visualization tools.
- Troubleshoot technical issues during practical sessions.
8. Student Engagement & Mentoring
- Encourage problem-solving, analytical thinking, and practical learning.
- Provide one-on-one guidance for student projects and assignments.
- Maintain an interactive and motivating classroom environment.
9. Reporting & Academic Coordination
- Maintain attendance, assessment records, project reports, and student progress data.
- Coordinate with the Academic Head / Centre Manager regarding batch performance.
- Participate in curriculum development and academic review meetings.
10. Workshops & Promotional Activities
- Conduct demo classes, workshops, seminars, and webinars.
- Support the admissions and marketing teams during student counselling sessions, career seminars, and promotional events.
11. Industry Research & Continuous Learning
- Stay updated with the latest developments in:
- Data Science
- Artificial Intelligence
- Machine Learning
- Generative AI
- Data Analytics tools and practices
- Incorporate industry case studies, datasets, and best practices into training.
Pay: ₹20,000.00 - ₹25,000.00 per month
Benefits:
Work Location: In person
