Data Science Trainer
3 days ago
**Job Description: Data Science Trainer**
**Position Overview**
**Key Responsibilities**
- **Training Delivery**: Conduct engaging and interactive training sessions on various data science topics, including but not limited to Python, R, SQL, machine learning, data visualization, and statistical analysis.
- **Curriculum Development**: Design and update course materials, including presentations, assignments, projects, and assessments to ensure they are current and relevant.
- **Hands-on Projects**: Develop practical, real-world projects and case studies to provide hands-on experience to learners.
- **Assessment & Feedback**: Evaluate students’ progress through assignments, projects, and exams, providing constructive feedback to help them improve.
- **Stay Updated**: Keep abreast of the latest trends and technologies in data science to ensure the training content remains cutting-edge.
- **Mentorship**: Provide guidance and support to students, helping them with career advice, resume building, and interview preparation.
- **Collaboration**: Work closely with other trainers and team members to ensure a cohesive learning experience.
**Qualifications**
- **Educational Background**: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. Ph.D. is a plus.
- **Experience**: At least 3-5 years of hands-on experience in data science roles. Prior experience in teaching or training is highly desirable.
- **Technical Skills**: Proficiency in Python, R, SQL, and familiarity with data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and Keras. Knowledge of data visualization tools like Tableau or Power BI is a plus.
- **Soft Skills**: Excellent communication and presentation skills. Ability to explain complex concepts in a simple and clear manner.
- **Certifications**: Relevant certifications (e.g., Certified Data Scientist, Microsoft Certified: Azure Data Scientist Associate) are an advantage.
**Benefits**:
- Health insurance
- Provident Fund
Schedule:
- Day shift
Work Location: In person
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