Role: Technical Trainer - Data Science
Location: Commutable London/Gloucester daily
Working environment: In-person Training, travel is required
Contract: Full time, 37.5 hrs per week
Package: competitive + benefits
Role Description:
Are you an experienced Technical Trainer with a strong background in practical data science, and ideally experience of teaching programming languages including Python and C.
You will be passionate about education, possess excellent communication skills, and have a proven track record of success. As a Technical Trainer, you will play a crucial role in empowering our learners with the skills and knowledge needed to excel in the rapidly evolving field of data science
Key Responsibilities:
Instruction and Delivery:
1. Conduct engaging and hands-on training sessions, workshops, and seminars for both non-data scientists and experienced data scientists.
2. Deliver training content effectively, ensuring that participants gain practical skills and knowledge applicable to their roles.
Curriculum Development:
3. Design and develop comprehensive training programs focused on practical data science, tailored to meet the needs of our learners.
Technical Expertise:
4. Demonstrate a deep understanding of data science principles, Python programming, and proficiency in C.
5. Share real-world examples and experiences from a software engineering environment to enhance the practical relevance of training content.
Assessment and Feedback:
6. Provide constructive feedback to participants, identifying areas for improvement and additional support.
Collaboration:
7. Work closely with cross-functional teams, including sales, and projects, to align training programs with customer goals.
Continuous Learning:
8. Stay abreast of industry trends, emerging technologies, and best practices to ensure training content remains current and relevant.
Qualifications:
9. Educated/Certified in Computer Science, Data Science, or a related field or equivalent industry experience.
10. Proven experience as a Technical Trainer with a focus on data science, Python, and C.
11. Strong programming skills in Python and C, with a solid understanding of software engineering principles.
Use of some of the following tools:
12. Visual Studio
13. Jupyter Notebooks
14. Git
15. Gitlabs
16. Docker
17. Kebernates
18. Apache Spark
19. MatLab
20. TensorFlow