IT trainer

A Data Science Trainer is responsible for teaching various modules of Data Science as per the curriculum.

Deliver training sessions, prepare learning materials, and assess the progress of learners.

The role demands strong expertise in data analytics, programming, machine learning, deep learning, and emerging AI technologies.

Data Science Trainer must be able to simplify complex technical concepts, demonstrate practical applications, and communicate effectively.

They play a key role in shaping learners into skilled data professionals who can work with real-world datasets and industry-relevant tools.

Roles & Responsibilities:

Conducting classroom or online lectures on Data Science, Data Analytics, PowerBi, Advance Excel, Machine Learning, Deep Learning, AI, SQL, Python, and related technologies.

Assigning and evaluating practical exercises, projects, and data-driven case studies.

Guiding students one-on-one with coding support, doubt-solving, and project mentoring.

Ensuring that the course curriculum is updated, practical, and aligned with current industry needs.

Collaborating with other trainers and content developers to create and improve training materials.

Maintaining accurate records of student performance, attendance, and progress reports.

Creating a positive, engaging, and hands-on learning environment for students.

Participating in faculty meetings, workshops, and continuous career development activities.

Keeping up-to-date with the latest advancements in Data Science tools, frameworks, and technologies.

Job Qualification & Skill Sets:

A Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.

Minimum 1 year of experience preferred.

Solid knowledge of Python programming, data analysis libraries and data visualization tools

(Matplotlib, Seaborn).

Proficiency in SQL for data extraction, manipulation, and analysis.

Knowledge of Deep Learning frameworks

Familiarity with AI concepts, NLP, computer vision, and data preprocessing techniques.

Excellent communication, presentation, and mentoring skills.

A passion for teaching and empowering students to build robust careers in Data Science.