Data Science Trainer

**Responsibilities**:
**Curriculum Development**:
Design and develop a well-structured and up-to-date data science training curriculum that covers fundamental data science concepts, data manipulation, statistical analysis, AI/ML algorithms, and model evaluation.

**Training Delivery**:
Conduct engaging and interactive training sessions, either in person or through virtual platforms, to impart data science and AI/ML knowledge effectively to participants.

**Hands-on Projects**:
**AI/ML Frameworks**:
Teach participants how to work with popular AI/ML frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, and Keras.

**Data Visualization**:
Instruct learners on data visualization techniques and tools, enabling them to present their findings effectively.

**Industry Use Cases**:
**Assessments and Feedback**:
Administer assessments and provide constructive feedback to participants, tracking their progress and supporting their continuous improvement.

**Stay Updated**:
Stay abreast of the latest advancements in data science, AI, and ML, incorporating cutting-edge technologies and techniques into the training curriculum.

**Customization**:
Collaborate with clients or organizations to customize training programs according to their specific needs and business requirements.

**Training Materials**:
Develop and maintain training materials, including presentations, code examples, and resources for participants' reference.

**Requirements**:

- Education: A bachelor's or master's degree in computer science, data science, statistics, or a related field. While formal education is valuable, practical experience and relevant certifications are equally significant.
- Data Science and AI/ML Experience: Extensive hands-on experience in data science and AI/ML projects, with proficiency in data manipulation, statistical analysis, and implementing AI/ML algorithms.
- Training Experience: Proven experience as a trainer or educator, preferably in the data science or AI/ML domain. Ability to convey complex technical concepts clearly to participants with varying levels of expertise.
- Technical Skills: Proficiency in programming languages like Python or R, and experience with popular data science libraries and AI/ML frameworks.
- Communication Skills: Excellent verbal and written communication skills to deliver training content and interact effectively with learners.
- Problem-Solving: Strong problem-solving abilities to guide learners in overcoming challenges encountered during their data science and AI/ML projects.
- Teaching Techniques: Familiarity with instructional techniques, adult learning principles, and training methodologies to create effective learning experiences.
- Passion for Teaching: A genuine passion for teaching and sharing knowledge, and a commitment to fostering a positive and supportive learning environment.

The Data Science with AI/ML Trainer plays a pivotal role in empowering learners with the skills and knowledge needed to succeed in the field of data science and AI/ML. By delivering high-quality training and promoting hands-on learning, you contribute significantly to the growth and success of individuals and organizations in the data-driven world.

**Job Types**: Full-time, Regular / Permanent, Fresher, Internship
Contract length: 6 months

**Salary**: ₹5,000.00 - ₹12,000.00 per month

**Benefits**:

- Cell phone reimbursement
- Internet reimbursement

Supplemental pay types:

- Commission pay
- Performance bonus
- Yearly bonus

Ability to commute/relocate:

- Ernakulam, Kerala: Reliably commute or planning to relocate before starting work (required)

**Experience**:

- total work: 1 year (preferred)

**Language**:

- English (required)