Key Responsibilities:

• Course Delivery:

• Lead hands-on sessions on data analysis, data pipelines, and machine learning models.
• Teach students practical skills in Python, R, SQL, and visualization tools like Tableau and Power BI.
• Facilitate project-based learning to develop real-world data science applications.

• Curriculum Development:

• Collaborate with NETSOL to refine and develop the data science curriculum.
• Incorporate machine learning frameworks (TensorFlow, PyTorch) and cloud platforms.
• Develop modules on data wrangling, feature engineering, and model deployment.

• Mentorship and Guidance:

• Mentor students through capstone data projects, ensuring their work is industry-relevant.
• Provide feedback to improve students' technical abilities and critical thinking.
• Support learners in building data science portfolios and preparing for data roles.

• Industry Insights:

• Share real-world experiences and case studies on data science applications.
• Highlight the latest trends in AI, big data, and automation.
• Introduce best practices for model validation and interpretability.

• Evaluation and Assessment:

• Design data challenges, machine learning competitions, and assessments to track performance.
• Provide consistent feedback and guidance.

• Requirements:

• Bachelor Computer Science / Data Science / Data Analytics / Economics / Statistics / Mathematics having 3 years’ experience in data analytics / big data technologies (Hadoop, Spark, etc.) / Data mining / Data Processing.
• Excellent communication and presentation skills.
• Previous experience in conducting technical training, workshops, or mentoring Will be a plus

• Preferred (Optional):

• Certifications in data science or cloud-based AI tools (IBM, AWS, Google certifications preferred but not mandatory).
• Experience with large-scale data architectures, LLMs, and NLP.